Tokenizer: roberta-base Model: roberta-base
	Train size: 80 Test size: 20


		-------------RUN 1-----------
			------------EPOCH 1---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 1.0, 'agreement': 0.15463917525773196, 'direct_attack': 0.06310679611650485, 'undercutter_attack': 0.0, 'partial': 0.0}, 'recall': {'support': 0.0035842293906810036, 'agreement': 0.5056179775280899, 'direct_attack': 0.3939393939393939, 'undercutter_attack': 0.0, 'partial': 0.0}, 'f1': {'support': 0.0071428571428571435, 'agreement': 0.2368421052631579, 'direct_attack': 0.1087866108786611, 'undercutter_attack': 0.0, 'partial': 0.0}, 'support': {'support': 279, 'agreement': 89, 'direct_attack': 33, 'undercutter_attack': 78, 'partial': 19}, 'micro_avg': {'precision': 0.11847389558232932, 'recall': 0.11847389558232932, 'f1': 0.11847389558232932, 'support': None}, 'macro_avg': {'precision': 0.24354919427484734, 'recall': 0.18062832017163297, 'f1': 0.07055431465693522, 'support': None}, 'weighted_avg': {'precision': 0.5920590579714513, 'recall': 0.11847389558232932, 'f1': 0.05353767604472694, 'support': None}}
Loss: tensor(0.7708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6983, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6751, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6783, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9847, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9774, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4962, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6977, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0601, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6744, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6738, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8761, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5817, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5983, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6890, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8785, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8683, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5751, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8912, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6765, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1817, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4765, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2844, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3915, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4994, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5971, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6569, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5553, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8873, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6900, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7998, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4880, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8926, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6751, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5998, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6831, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6921, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6926, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2680, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5427, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5719, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1652, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4693, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4754, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6705, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8774, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2738, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4957, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3844, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9955, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2956, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3912, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2844, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1927, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6683, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8868, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6774, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8994, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2898, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9560, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7713, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4757, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4761, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8784, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4374, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3915, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0997, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1885, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8978, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2720, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2957, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7616, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3671, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8843, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3826, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7950, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2921, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9912, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0983, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0632, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8761, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9784, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0757, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5632, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6632, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5985, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5553, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1783, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2798, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5950, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8739, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0798, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0116, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 2---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7853107344632768, 'agreement': 0.37254901960784315, 'direct_attack': 0.05128205128205128, 'undercutter_attack': 0.14285714285714285, 'partial': 0.09302325581395349}, 'recall': {'support': 0.4982078853046595, 'agreement': 0.8539325842696629, 'direct_attack': 0.06060606060606061, 'undercutter_attack': 0.0641025641025641, 'partial': 0.21052631578947367}, 'f1': {'support': 0.6096491228070176, 'agreement': 0.5187713310580205, 'direct_attack': 0.05555555555555555, 'undercutter_attack': 0.08849557522123894, 'partial': 0.12903225806451613}, 'support': {'support': 279, 'agreement': 89, 'direct_attack': 33, 'undercutter_attack': 78, 'partial': 19}, 'micro_avg': {'precision': 0.4538152610441767, 'recall': 0.4538152610441767, 'f1': 0.4538152610441767, 'support': None}, 'macro_avg': {'precision': 0.2890044408048535, 'recall': 0.3374750820144842, 'f1': 0.28030076854126973, 'support': None}, 'weighted_avg': {'precision': 0.5358657918794824, 'recall': 0.4538152610441767, 'f1': 0.4567276201428464, 'support': None}}
Loss: tensor(0.6335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2860, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7797, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1915, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1713, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2553, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0481, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0806, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8983, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1890, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0769, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6997, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5739, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0935, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2773, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0997, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9844, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7374, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5994, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6885, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4873, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4997, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5929, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7632, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2985, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2844, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1739, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2900, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0840, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4773, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0922, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1831, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3862, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2569, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2511, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2777, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5791, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7739, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3983, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6840, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0922, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1972, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9754, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4971, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2813, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0761, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7994, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6791, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0705, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0972, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1831, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1972, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5705, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8912, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2971, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5950, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6754, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9652, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7740, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5797, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0898, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6654, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8922, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7641, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8616, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6635, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3912, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2774, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5950, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4994, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2632, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4560, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8801, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2641, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7987, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1796, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2844, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0965, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4569, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2844, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9680, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1978, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4813, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3844, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2957, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2947, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7840, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2885, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7871, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1751, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5997, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0996, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 3---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6623711340206185, 'agreement': 0.6231884057971014, 'direct_attack': 0.2857142857142857, 'undercutter_attack': 0.1, 'partial': 0.0}, 'recall': {'support': 0.921146953405018, 'agreement': 0.48314606741573035, 'direct_attack': 0.18181818181818182, 'undercutter_attack': 0.02564102564102564, 'partial': 0.0}, 'f1': {'support': 0.7706146926536732, 'agreement': 0.5443037974683544, 'direct_attack': 0.2222222222222222, 'undercutter_attack': 0.04081632653061225, 'partial': 0.0}, 'support': {'support': 279, 'agreement': 89, 'direct_attack': 33, 'undercutter_attack': 78, 'partial': 19}, 'micro_avg': {'precision': 0.6184738955823293, 'recall': 0.6184738955823293, 'f1': 0.6184738955823293, 'support': None}, 'macro_avg': {'precision': 0.3342547651064011, 'recall': 0.32235044565599114, 'f1': 0.3155914077749724, 'support': None}, 'weighted_avg': {'precision': 0.5170559958559559, 'recall': 0.6184738955823293, 'f1': 0.5501235823850993, 'support': None}}
Loss: tensor(1.5794, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2847, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7950, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0965, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3903, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2922, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0652, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9965, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8840, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2915, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2777, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9994, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0713, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0837, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3739, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7947, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2791, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0680, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6751, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0965, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0481, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2903, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1880, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5997, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0837, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9511, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3922, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8751, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0873, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3374, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5427, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0671, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1798, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0922, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5750, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4906, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0740, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5671, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0560, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0701, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0560, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1873, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0956, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2713, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5873, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0862, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2890, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2806, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0785, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0773, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2826, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4744, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0826, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0730, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2873, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3794, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1784, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9761, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0511, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5847, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0927, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2947, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1860, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4900, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2885, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4730, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2977, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2632, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2765, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2753, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1965, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1511, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2826, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3773, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1662, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0900, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0754, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0701, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9978, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0761, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8972, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0947, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0262, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 4---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7614678899082569, 'agreement': 0.41818181818181815, 'direct_attack': 0.11627906976744186, 'undercutter_attack': 0.21428571428571427, 'partial': 0.15384615384615385}, 'recall': {'support': 0.5949820788530465, 'agreement': 0.25842696629213485, 'direct_attack': 0.6060606060606061, 'undercutter_attack': 0.038461538461538464, 'partial': 0.3157894736842105}, 'f1': {'support': 0.6680080482897385, 'agreement': 0.3194444444444445, 'direct_attack': 0.1951219512195122, 'undercutter_attack': 0.06521739130434782, 'partial': 0.20689655172413793}, 'support': {'support': 279, 'agreement': 89, 'direct_attack': 33, 'undercutter_attack': 78, 'partial': 19}, 'micro_avg': {'precision': 0.43775100401606426, 'recall': 0.43775100401606426, 'f1': 0.4377510040160642, 'support': None}, 'macro_avg': {'precision': 0.33281212919787695, 'recall': 0.36274413267030725, 'f1': 0.29093767739643617, 'support': None}, 'weighted_avg': {'precision': 0.5484785041009512, 'recall': 0.43775100401606426, 'f1': 0.4623731253476592, 'support': None}}
Loss: tensor(0.4943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1374, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1660, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8873, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0900, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1701, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0813, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0983, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2744, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2785, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0797, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5940, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5798, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0753, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2978, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0977, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1662, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0817, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0977, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1635, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0481, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1852, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1890, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9796, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0761, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1915, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0553, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4751, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7950, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0871, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0785, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0977, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0915, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4862, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0635, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0994, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0987, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2978, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2601, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1862, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6813, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4847, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3929, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8862, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0927, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5784, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7831, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3997, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3898, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3904, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0926, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1604, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0794, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2994, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0754, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1777, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 5---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6617647058823529, 'agreement': 0.6086956521739131, 'direct_attack': 0.3181818181818182, 'undercutter_attack': 0.11764705882352941, 'partial': 0.125}, 'recall': {'support': 0.8064516129032258, 'agreement': 0.47191011235955055, 'direct_attack': 0.21212121212121213, 'undercutter_attack': 0.07692307692307693, 'partial': 0.10526315789473684}, 'f1': {'support': 0.726978998384491, 'agreement': 0.5316455696202531, 'direct_attack': 0.2545454545454546, 'undercutter_attack': 0.0930232558139535, 'partial': 0.11428571428571428}, 'support': {'support': 279, 'agreement': 89, 'direct_attack': 33, 'undercutter_attack': 78, 'partial': 19}, 'micro_avg': {'precision': 0.5662650602409639, 'recall': 0.5662650602409639, 'f1': 0.5662650602409639, 'support': None}, 'macro_avg': {'precision': 0.36625784701232267, 'recall': 0.33453383444036044, 'f1': 0.3440957985299733, 'support': None}, 'weighted_avg': {'precision': 0.5238107160098193, 'recall': 0.5662650602409639, 'f1': 0.5380940537558081, 'support': None}}
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4997, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1903, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0862, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0660, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0713, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9813, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0957, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0791, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2616, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0965, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1754, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1769, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3940, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0671, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0843, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0994, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0947, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4965, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0769, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0765, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8971, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0683, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3922, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2331, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 6---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7238095238095238, 'agreement': 0.46153846153846156, 'direct_attack': 0.136, 'undercutter_attack': 0.08695652173913043, 'partial': 0.12903225806451613}, 'recall': {'support': 0.5448028673835126, 'agreement': 0.4044943820224719, 'direct_attack': 0.5151515151515151, 'undercutter_attack': 0.02564102564102564, 'partial': 0.42105263157894735}, 'f1': {'support': 0.621676891615542, 'agreement': 0.4311377245508982, 'direct_attack': 0.21518987341772153, 'undercutter_attack': 0.039603960396039604, 'partial': 0.19753086419753085}, 'support': {'support': 279, 'agreement': 89, 'direct_attack': 33, 'undercutter_attack': 78, 'partial': 19}, 'micro_avg': {'precision': 0.43172690763052207, 'recall': 0.43172690763052207, 'f1': 0.43172690763052207, 'support': None}, 'macro_avg': {'precision': 0.30746735303032635, 'recall': 0.3822284843554945, 'f1': 0.30102786283554644, 'support': None}, 'weighted_avg': {'precision': 0.51554618839088, 'recall': 0.43172690763052207, 'f1': 0.45333849678553234, 'support': None}}
Loss: tensor(0.0492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0750, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0753, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5831, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0796, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0898, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0791, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0740, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0705, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1750, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0935, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0840, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0840, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0660, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0956, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0929, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8640e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0947, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1705, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0977, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1983, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0522, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 7---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6843657817109144, 'agreement': 0.6417910447761194, 'direct_attack': 0.21568627450980393, 'undercutter_attack': 0.11764705882352941, 'partial': 0.0}, 'recall': {'support': 0.8315412186379928, 'agreement': 0.48314606741573035, 'direct_attack': 0.3333333333333333, 'undercutter_attack': 0.05128205128205128, 'partial': 0.0}, 'f1': {'support': 0.7508090614886731, 'agreement': 0.5512820512820513, 'direct_attack': 0.26190476190476186, 'undercutter_attack': 0.07142857142857141, 'partial': 0.0}, 'support': {'support': 279, 'agreement': 89, 'direct_attack': 33, 'undercutter_attack': 78, 'partial': 19}, 'micro_avg': {'precision': 0.5823293172690763, 'recall': 0.5823293172690763, 'f1': 0.5823293172690763, 'support': None}, 'macro_avg': {'precision': 0.3318980319640734, 'recall': 0.33986053413382156, 'f1': 0.3270848892208115, 'support': None}, 'weighted_avg': {'precision': 0.5308264532720453, 'recall': 0.5823293172690763, 'f1': 0.5476990289833897, 'support': None}}
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0427, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8761e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8761e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5268e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6853e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7106e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2977, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7671e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0850, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 8---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.815068493150685, 'agreement': 0.3423913043478261, 'direct_attack': 0.22641509433962265, 'undercutter_attack': 0.12149532710280374, 'partial': 0.125}, 'recall': {'support': 0.4265232974910394, 'agreement': 0.7078651685393258, 'direct_attack': 0.36363636363636365, 'undercutter_attack': 0.16666666666666666, 'partial': 0.05263157894736842}, 'f1': {'support': 0.5599999999999999, 'agreement': 0.4615384615384615, 'direct_attack': 0.27906976744186046, 'undercutter_attack': 0.14054054054054055, 'partial': 0.07407407407407407}, 'support': {'support': 279, 'agreement': 89, 'direct_attack': 33, 'undercutter_attack': 78, 'partial': 19}, 'micro_avg': {'precision': 0.41767068273092367, 'recall': 0.41767068273092367, 'f1': 0.41767068273092367, 'support': None}, 'macro_avg': {'precision': 0.32607404378818744, 'recall': 0.3434646150561528, 'f1': 0.30304456871898733, 'support': None}, 'weighted_avg': {'precision': 0.5566270467936223, 'recall': 0.4176706827309236, 'f1': 0.4395497891005503, 'support': None}}
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0794, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1041e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4139e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6167e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3615e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5643e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2464e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7630e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4935e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6581e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8165e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 9---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7423076923076923, 'agreement': 0.6229508196721312, 'direct_attack': 0.11450381679389313, 'undercutter_attack': 0.03225806451612903, 'partial': 0.2}, 'recall': {'support': 0.6917562724014337, 'agreement': 0.42696629213483145, 'direct_attack': 0.45454545454545453, 'undercutter_attack': 0.01282051282051282, 'partial': 0.15789473684210525}, 'f1': {'support': 0.7161410018552875, 'agreement': 0.5066666666666667, 'direct_attack': 0.18292682926829268, 'undercutter_attack': 0.01834862385321101, 'partial': 0.17647058823529413}, 'support': {'support': 279, 'agreement': 89, 'direct_attack': 33, 'undercutter_attack': 78, 'partial': 19}, 'micro_avg': {'precision': 0.5020080321285141, 'recall': 0.5020080321285141, 'f1': 0.5020080321285141, 'support': None}, 'macro_avg': {'precision': 0.3424040786579691, 'recall': 0.34879665374886754, 'f1': 0.3201107419757504, 'support': None}, 'weighted_avg': {'precision': 0.5474723375323742, 'recall': 0.5020080321285141, 'f1': 0.5134887390639221, 'support': None}}
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0557e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5248e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5259e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0990e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3796e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6067e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0566e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3191e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7983e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4371e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9244e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3796e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3897e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9779e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5128e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2655e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8337e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6157e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6449e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1646e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4784e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1232e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4218e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5229e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6652e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9446e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4744e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8559e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2343e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8892e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9798e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2735e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6258e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1332e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7548e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0748e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7478e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1767e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 10---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7433333333333333, 'agreement': 0.5487804878048781, 'direct_attack': 0.30952380952380953, 'undercutter_attack': 0.08064516129032258, 'partial': 0.25}, 'recall': {'support': 0.7992831541218638, 'agreement': 0.5056179775280899, 'direct_attack': 0.3939393939393939, 'undercutter_attack': 0.0641025641025641, 'partial': 0.15789473684210525}, 'f1': {'support': 0.770293609671848, 'agreement': 0.5263157894736842, 'direct_attack': 0.3466666666666667, 'undercutter_attack': 0.07142857142857142, 'partial': 0.1935483870967742}, 'support': {'support': 279, 'agreement': 89, 'direct_attack': 33, 'undercutter_attack': 78, 'partial': 19}, 'micro_avg': {'precision': 0.5803212851405622, 'recall': 0.5803212851405622, 'f1': 0.5803212851405622, 'support': None}, 'macro_avg': {'precision': 0.38645655839046866, 'recall': 0.3841675653068034, 'f1': 0.3816506048675089, 'support': None}, 'weighted_avg': {'precision': 0.557200947207962, 'recall': 0.5803212851405622, 'f1': 0.5671543580077726, 'support': None}}
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5431e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5613e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9567e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2786e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7650e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5299e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4209e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2110e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5249e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1414e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8165e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7166e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4239e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3976e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8609e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3309e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6419e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7841e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7974e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3906e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9344e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3309e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8519e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0254e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4421e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4129e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4339e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0545e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1555e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4702e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3784e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9839e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9122e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1162e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9748e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8074e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2756e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4644e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1919e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9737e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7194e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4662e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8004e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2251e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8973e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8992e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2836e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6143e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6379e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3583e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4421e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3806e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1938e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9900e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7539e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4087e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6065e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6802e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1989e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2767e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7257e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7075e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9213e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1384e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3382e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6096e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1889e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2806e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0818e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1865e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7227e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4400e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4863e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0586e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9415e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8093e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4136e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6610e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8850e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7096e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3903e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7095e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0394e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6912e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2613e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5470e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5771e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4845e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9677e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7166e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2068e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1383e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1838e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6307e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7406e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8770e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0182e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7315e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6882e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4279e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1211e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3654e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6903e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6891e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 11---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7384105960264901, 'agreement': 0.6111111111111112, 'direct_attack': 0.26666666666666666, 'undercutter_attack': 0.11940298507462686, 'partial': 0.3333333333333333}, 'recall': {'support': 0.7992831541218638, 'agreement': 0.4943820224719101, 'direct_attack': 0.36363636363636365, 'undercutter_attack': 0.10256410256410256, 'partial': 0.21052631578947367}, 'f1': {'support': 0.7676419965576592, 'agreement': 0.546583850931677, 'direct_attack': 0.30769230769230765, 'undercutter_attack': 0.1103448275862069, 'partial': 0.2580645161290323}, 'support': {'support': 279, 'agreement': 89, 'direct_attack': 33, 'undercutter_attack': 78, 'partial': 19}, 'micro_avg': {'precision': 0.5843373493975904, 'recall': 0.5843373493975904, 'f1': 0.5843373493975904, 'support': None}, 'macro_avg': {'precision': 0.41378493844244557, 'recall': 0.39407839171674275, 'f1': 0.3980654997793766, 'support': None}, 'weighted_avg': {'precision': 0.5719923922679394, 'recall': 0.5843373493975904, 'f1': 0.5752651571978474, 'support': None}}
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6640e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7236e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7285e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4915e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9213e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9567e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5943e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1956e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0252e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2765e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5491e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5955e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3473e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3269e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7701e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1039e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4856e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6791e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6337e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8579e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2797e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4015e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9840e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2110e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3370e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6943e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2664e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7960e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8678e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8468e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6337e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4793e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7629e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5207e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0829e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3168e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4784e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2019e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3714e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4765e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6196e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9325e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2501e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6833e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0152e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2301e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4735e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9092e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6772e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6991e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5338e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0606e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8004e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2937e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4027e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7983e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8033e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5854e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8740e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6176e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9032e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6641e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4512e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4319e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7255e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9779e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5913e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9507e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6770e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4127e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7699e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2059e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6154e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5077e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5135e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7760e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3249e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1393e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2715e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4218e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3319e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4178e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7700e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3503e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2341e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5135e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2210e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2189e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8366e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7839e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0100e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6742e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8901e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2896e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1744e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8314e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9849e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1494e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2480e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7993e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8487e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5559e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5794e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4945e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5450e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8263e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2664e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0687e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4218e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9889e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4734e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6438e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9767e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0606e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3509e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0556e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6416e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8032e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8326e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3088e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9375e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1384e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4923e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8538e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4290e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2816e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3361e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7536e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1251e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9910e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8980e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7720e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1584e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7830e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6083e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0506e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0263e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6822e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5217e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8314e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9988e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7426e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0797e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4239e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3218e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9295e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9061e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3775e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6749e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1242e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6903e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6770e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9958e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9201e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7106e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1584e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5843e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3077e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6427e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2301e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7285e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9516e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 12---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7408637873754153, 'agreement': 0.569620253164557, 'direct_attack': 0.2926829268292683, 'undercutter_attack': 0.078125, 'partial': 0.23076923076923078}, 'recall': {'support': 0.7992831541218638, 'agreement': 0.5056179775280899, 'direct_attack': 0.36363636363636365, 'undercutter_attack': 0.0641025641025641, 'partial': 0.15789473684210525}, 'f1': {'support': 0.7689655172413793, 'agreement': 0.5357142857142858, 'direct_attack': 0.32432432432432434, 'undercutter_attack': 0.07042253521126761, 'partial': 0.18749999999999997}, 'support': {'support': 279, 'agreement': 89, 'direct_attack': 33, 'undercutter_attack': 78, 'partial': 19}, 'micro_avg': {'precision': 0.5783132530120482, 'recall': 0.5783132530120482, 'f1': 0.5783132530120482, 'support': None}, 'macro_avg': {'precision': 0.3824122396276943, 'recall': 0.37810695924619736, 'f1': 0.3773853324982514, 'support': None}, 'weighted_avg': {'precision': 0.5572973919264411, 'recall': 0.5783132530120482, 'f1': 0.5662211068034092, 'support': None}}
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2443e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0010e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1947e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3531e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4369e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3039e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2280e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7718e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3379e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3714e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0869e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8093e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6710e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8405e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2583e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8980e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9555e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7005e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0929e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0424e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7648e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9789e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3594e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4542e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2259e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2523e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5912e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6731e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2534e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8202e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2220e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7064e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7569e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9395e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7608e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2038e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6024e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4236e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2825e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2674e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3016e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1109e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7317e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7781e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0999e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7388e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3087e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0403e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1707e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6174e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8557e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9800e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3149e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1847e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3098e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2634e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2665e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2986e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1169e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6631e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1230e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4351e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0484e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6325e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5126e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8544e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5611e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1481e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9304e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9567e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6891e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0000e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2896e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3267e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3612e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4357e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3055e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3431e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3431e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7175e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5510e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4280e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6034e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5680e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6974e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5703e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2200e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9516e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7678e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6931e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9648e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8356e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6065e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7133e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1868e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8961e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0646e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4175e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5609e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8375e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0978e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0162e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2604e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3744e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8770e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9830e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2077e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8998e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2946e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6125e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7176e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1463e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9262e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5410e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0473e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0909e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0526e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2352e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7778e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8002e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3745e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9707e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2686e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5680e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8223e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8427e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4278e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3493e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7363e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5490e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5438e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1495e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8105e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4106e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1139e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4551e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2241e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2836e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4854e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4703e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9364e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8626e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7749e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6567e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7194e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2562e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7196e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7548e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5471e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3795e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1995e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7627e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9446e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1714e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8202e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9891e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4229e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3085e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3379e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6428e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5992e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3894e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1723e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5347e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7529e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2976e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6097e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7073e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8809e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0857e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2009e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3331e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8172e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0373e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1816e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3129e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6185e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4790e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4592e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2865e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0182e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3349e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5123e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3724e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2504e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7034e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5538e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7960e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3098e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0373e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5551e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6823e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9573e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2664e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8992e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9950e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3146e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4390e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3744e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1814e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3028e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7983e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0374e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1766e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6933e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5622e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0857e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8989e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 13---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7417218543046358, 'agreement': 0.5555555555555556, 'direct_attack': 0.3076923076923077, 'undercutter_attack': 0.078125, 'partial': 0.25}, 'recall': {'support': 0.8028673835125448, 'agreement': 0.5056179775280899, 'direct_attack': 0.36363636363636365, 'undercutter_attack': 0.0641025641025641, 'partial': 0.15789473684210525}, 'f1': {'support': 0.7710843373493975, 'agreement': 0.5294117647058825, 'direct_attack': 0.33333333333333337, 'undercutter_attack': 0.07042253521126761, 'partial': 0.1935483870967742}, 'support': {'support': 279, 'agreement': 89, 'direct_attack': 33, 'undercutter_attack': 78, 'partial': 19}, 'micro_avg': {'precision': 0.5803212851405622, 'recall': 0.5803212851405622, 'f1': 0.5803212851405622, 'support': None}, 'macro_avg': {'precision': 0.3866189435104998, 'recall': 0.3788238051243336, 'f1': 0.3795600715393311, 'support': None}, 'weighted_avg': {'precision': 0.5569928472877188, 'recall': 0.5803212851405622, 'f1': 0.567109546748239, 'support': None}}
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0685e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8768e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7489e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8271e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8474e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2918e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6973e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4106e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0203e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6328e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4288e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0564e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5650e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6891e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7436e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4802e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7969e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7899e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9565e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7578e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8004e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8556e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4078e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6400e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8317e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9837e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8483e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6702e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3328e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1139e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6691e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7456e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5741e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9646e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2713e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9909e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5278e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5974e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7245e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6731e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6437e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2552e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7436e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3297e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5398e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4108e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7739e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3008e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1390e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7588e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8154e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1353e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4024e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9396e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3994e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9749e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6882e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8475e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0451e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3897e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3582e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7154e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2925e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7497e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3027e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1160e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8375e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6567e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9879e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7718e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9395e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0080e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5499e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6961e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3116e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2340e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4206e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2362e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1078e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7514e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3652e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8074e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6900e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5681e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5901e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7657e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4108e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7800e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7427e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0101e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0010e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5337e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7850e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5589e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6679e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4278e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9122e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4662e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3812e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4147e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9427e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1290e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1807e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1078e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6621e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9301e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1393e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3639e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5228e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4712e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2298e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7333e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0303e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1120e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0905e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3055e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1080e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2988e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6045e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0868e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2937e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0576e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0040e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9728e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0261e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8526e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0384e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0736e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9080e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6500e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6639e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2441e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3046e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1635e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9374e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8982e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5438e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7700e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2492e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4400e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9694e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4772e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4569e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4145e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0433e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8111e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0775e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9355e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0615e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9121e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4521e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8882e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7892e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7990e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0415e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4348e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2068e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5053e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9132e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1775e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4884e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0424e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6446e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1511e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1342e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7084e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5783e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6658e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0161e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6365e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3461e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2056e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2837e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4239e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2088e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3400e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4811e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6278e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2370e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9283e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2722e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7609e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4238e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9647e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9876e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8628e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8922e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2604e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0606e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8133e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2865e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3851e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1956e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7406e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8417e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5813e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8610e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7215e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4327e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7881e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2056e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3470e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0987e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4751e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3058e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2886e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2692e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2532e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1351e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3055e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1753e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5710e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4720e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7780e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5420e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2423e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1251e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1714e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2692e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0284e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8234e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0173e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9243e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5064e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 14---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7408637873754153, 'agreement': 0.6164383561643836, 'direct_attack': 0.2608695652173913, 'undercutter_attack': 0.109375, 'partial': 0.2857142857142857}, 'recall': {'support': 0.7992831541218638, 'agreement': 0.5056179775280899, 'direct_attack': 0.36363636363636365, 'undercutter_attack': 0.08974358974358974, 'partial': 0.21052631578947367}, 'f1': {'support': 0.7689655172413793, 'agreement': 0.5555555555555557, 'direct_attack': 0.3037974683544304, 'undercutter_attack': 0.09859154929577464, 'partial': 0.24242424242424243}, 'support': {'support': 279, 'agreement': 89, 'direct_attack': 33, 'undercutter_attack': 78, 'partial': 19}, 'micro_avg': {'precision': 0.5843373493975904, 'recall': 0.5843373493975904, 'f1': 0.5843373493975904, 'support': None}, 'macro_avg': {'precision': 0.4026521988942952, 'recall': 0.39376148016387613, 'f1': 0.3938668665742765, 'support': None}, 'weighted_avg': {'precision': 0.5705472438897919, 'recall': 0.5843373493975904, 'f1': 0.574914340685977, 'support': None}}
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3139e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5005e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1087e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7791e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2410e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4330e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8959e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7214e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9879e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5872e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5256e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5610e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6939e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8406e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6972e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4822e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4320e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0858e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1605e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4590e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4539e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6721e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6446e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6658e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4269e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2786e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0421e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0706e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4714e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1796e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6428e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3190e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1453e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2683e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6727e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8142e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8483e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4884e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0918e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1454e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8678e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1965e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0969e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1804e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8909e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2473e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4560e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1584e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2177e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1947e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4451e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9020e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2079e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7852e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1877e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8246e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2047e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3894e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8042e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0303e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0412e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0351e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1029e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7142e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9452e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2856e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0784e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4127e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3140e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0403e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6216e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9737e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1605e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1323e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5174e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0524e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5580e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3367e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9201e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4542e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5417e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0261e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8788e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4863e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9859e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3540e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3872e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4057e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0596e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1805e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5840e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1757e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6588e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6600e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6618e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7285e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2310e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4296e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6367e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5035e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5519e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5629e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3237e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8444e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2635e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0122e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4117e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1411e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5538e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7294e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5864e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6004e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6702e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0170e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4084e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6246e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5156e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3503e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3019e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7938e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0605e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7577e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7054e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6812e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4320e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6667e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1190e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0321e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3046e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6567e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3379e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3851e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1926e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5610e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5913e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0887e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7003e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1977e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6570e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2937e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6658e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9121e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6518e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2107e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3118e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3440e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6659e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4417e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8294e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8729e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5559e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9003e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3118e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9271e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5144e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4187e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1714e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2865e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7376e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4638e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8738e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3824e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8090e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8665e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0827e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6115e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3046e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0131e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2877e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4841e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5762e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7590e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3249e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4139e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3886e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5429e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4460e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4720e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2663e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7156e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9304e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5153e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7233e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8565e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5005e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7427e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6243e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8940e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6185e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4218e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9062e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0382e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5062e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0948e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1595e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9543e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5750e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4965e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9434e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6852e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2228e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0754e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2190e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6831e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8053e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7950e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2238e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0857e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2007e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8643e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0464e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4258e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4245e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8213e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3630e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2310e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0403e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8223e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7759e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2761e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9869e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3036e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2177e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5098e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8253e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3027e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8395e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5698e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2086e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1009e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1938e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9565e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2168e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2653e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2029e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2540e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8081e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4501e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9679e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9201e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5510e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1874e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2138e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6446e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5992e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3742e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8244e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1323e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8808e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5992e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3570e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9301e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7809e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7597e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5609e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3209e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9513e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2582e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4893e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4872e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4318e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1895e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7333e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3790e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2855e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4993e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6378e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4327e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1281e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5983e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5226e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0343e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3087e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6606e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1260e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5338e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9543e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4396e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3078e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3309e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9271e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7687e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5317e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1381e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9375e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5097e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7717e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7597e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9779e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6113e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1695e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4741e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3137e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4136e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6476e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 15---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7392739273927392, 'agreement': 0.569620253164557, 'direct_attack': 0.3076923076923077, 'undercutter_attack': 0.07692307692307693, 'partial': 0.25}, 'recall': {'support': 0.8028673835125448, 'agreement': 0.5056179775280899, 'direct_attack': 0.36363636363636365, 'undercutter_attack': 0.0641025641025641, 'partial': 0.15789473684210525}, 'f1': {'support': 0.7697594501718212, 'agreement': 0.5357142857142858, 'direct_attack': 0.33333333333333337, 'undercutter_attack': 0.06993006993006994, 'partial': 0.1935483870967742}, 'support': {'support': 279, 'agreement': 89, 'direct_attack': 33, 'undercutter_attack': 78, 'partial': 19}, 'micro_avg': {'precision': 0.5803212851405622, 'recall': 0.5803212851405622, 'f1': 0.5803212851405622, 'support': None}, 'macro_avg': {'precision': 0.38870191303453616, 'recall': 0.3788238051243336, 'f1': 0.3804571052492569, 'support': None}, 'weighted_avg': {'precision': 0.5579467357993292, 'recall': 0.5803212851405622, 'f1': 0.5674165117186621, 'support': None}}
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9486e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6295e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2855e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8841e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4159e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1009e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3824e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7469e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7338e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1302e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7074e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2411e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2976e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8225e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7657e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6851e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2782e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0676e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7517e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9171e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6225e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3509e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9373e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2822e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5659e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9706e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7233e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8204e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5208e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9210e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1450e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9945e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6670e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0455e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6628e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9755e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1524e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3397e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3291e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2108e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0809e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0837e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7427e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4366e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9361e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2843e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7862e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7739e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5728e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1300e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7415e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0635e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3158e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7052e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1905e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5468e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4945e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7060e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9097e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2775e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5126e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5137e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0361e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3280e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0784e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9495e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2058e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8698e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8847e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5862e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4469e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3864e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6449e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4823e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2095e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4275e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4539e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6095e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1874e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4188e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2873e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6490e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5207e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1251e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9737e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6407e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9050e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0179e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6104e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7164e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3149e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3518e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6043e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9906e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0261e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3924e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7809e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2964e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4145e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4490e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1129e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3479e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9564e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0442e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0421e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8323e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1026e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7366e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0845e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9646e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9504e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2549e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4305e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6757e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7294e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5740e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1131e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0412e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2462e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5580e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4880e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2846e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7468e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5001e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5689e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2241e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9249e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1372e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1866e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4390e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9496e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3804e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3352e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1756e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0534e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4127e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1260e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1835e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5267e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4729e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9271e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3372e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3267e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3149e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5377e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2783e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7203e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1260e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2640e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3548e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8241e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1541e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6881e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2350e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0815e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5235e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5477e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6528e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6052e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4296e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0451e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6661e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1838e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3237e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9383e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2410e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5014e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9265e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1502e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6891e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2492e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6930e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1027e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3735e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8153e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4278e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0899e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5304e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1057e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4759e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6195e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1120e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5438e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9867e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8401e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5901e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7333e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7619e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2806e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4510e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0058e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4621e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4872e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9746e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1372e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5650e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3057e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7324e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6848e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2643e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3842e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6091e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2834e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6688e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5610e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0757e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5023e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5097e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1241e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3578e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1000e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0875e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4408e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2129e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6636e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8989e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9364e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0845e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0127e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1502e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2198e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1057e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9482e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3077e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9113e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8163e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1684e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8401e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9413e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1987e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4984e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3482e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5629e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9119e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4296e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4175e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6174e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9767e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1333e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1995e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5689e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1332e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7840e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4681e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4266e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3863e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6305e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3784e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0503e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1472e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7899e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2362e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1187e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9182e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8889e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5598e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2086e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9807e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5389e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7224e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8414e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4539e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8150e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2259e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5456e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3639e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4408e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7787e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0676e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0551e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1172e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4307e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1783e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8556e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2995e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4541e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4742e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8427e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3896e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1008e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2095e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3996e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0897e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4145e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9707e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2985e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7651e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0672e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4400e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6830e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1283e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2674e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0282e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1826e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8879e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0058e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9900e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1057e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1411e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7726e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1952e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0875e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6061e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6779e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8059e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4590e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7427e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6891e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8789e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7838e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7004e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7666e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5719e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4763e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3509e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2504e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3349e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0121e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0908e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3328e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8223e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5912e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2622e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0857e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8068e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4338e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6690e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2443e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9019e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1208e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7650e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8959e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4934e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9655e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2936e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7507e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1211e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6628e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2744e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0563e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7696e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1441e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8729e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2216e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2458e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 16---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7392739273927392, 'agreement': 0.5769230769230769, 'direct_attack': 0.3076923076923077, 'undercutter_attack': 0.078125, 'partial': 0.2857142857142857}, 'recall': {'support': 0.8028673835125448, 'agreement': 0.5056179775280899, 'direct_attack': 0.36363636363636365, 'undercutter_attack': 0.0641025641025641, 'partial': 0.21052631578947367}, 'f1': {'support': 0.7697594501718212, 'agreement': 0.5389221556886228, 'direct_attack': 0.33333333333333337, 'undercutter_attack': 0.07042253521126761, 'partial': 0.24242424242424243}, 'support': {'support': 279, 'agreement': 89, 'direct_attack': 33, 'undercutter_attack': 78, 'partial': 19}, 'micro_avg': {'precision': 0.5823293172690763, 'recall': 0.5823293172690763, 'f1': 0.5823293172690763, 'support': None}, 'macro_avg': {'precision': 0.3975457195444819, 'recall': 0.3893501209138073, 'f1': 0.3909723433658575, 'support': None}, 'weighted_avg': {'precision': 0.5608027051629431, 'recall': 0.5823293172690763, 'f1': 0.5699316803348695, 'support': None}}
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2359e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5235e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8807e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2220e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7060e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6065e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8271e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3972e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2884e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6930e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8253e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5801e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5849e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4638e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8704e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7901e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9582e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8074e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4136e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0430e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8998e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5912e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4660e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6961e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8365e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4005e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9824e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6234e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3185e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3349e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2373e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6540e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2289e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2367e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9858e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8898e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9374e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6091e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2943e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3582e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9746e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5096e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3094e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2670e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1321e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5095e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4460e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8998e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6052e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1360e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1271e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4651e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8465e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2540e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3682e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1762e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5023e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4275e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5801e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8163e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5689e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1602e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6799e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5053e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7881e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1221e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9392e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8250e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5598e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7726e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8435e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2147e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1251e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5568e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9604e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1814e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2643e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0936e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9201e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4925e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2431e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6122e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6749e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7514e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2298e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4166e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9001e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6114e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4132e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6909e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4841e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7393e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5840e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5256e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5471e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8464e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0089e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8189e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2633e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7969e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9413e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1138e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7311e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1096e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6697e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7942e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7548e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1532e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6367e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9827e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4339e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2481e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0584e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3209e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4561e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5105e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4275e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4126e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6303e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6933e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9028e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2238e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7580e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6969e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4378e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6182e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7000e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3197e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5901e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8312e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9846e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0686e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0373e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7214e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2289e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9857e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9182e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8545e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1582e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6124e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6204e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0957e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4063e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7750e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1368e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2216e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9292e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0342e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2794e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6770e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6900e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6061e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2311e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5721e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2735e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5546e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2755e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9737e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2177e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2964e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1411e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6739e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3008e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5852e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8528e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1100e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8286e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5287e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1610e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7908e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2904e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7809e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9122e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8150e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0239e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9867e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0714e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4511e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4205e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7696e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3349e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4761e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5650e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1299e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4054e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3318e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3048e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1554e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1493e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5244e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3397e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6104e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8626e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1995e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8414e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3993e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4830e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8768e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1755e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5680e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3863e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0606e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3094e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1402e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8505e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4448e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8850e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1489e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1641e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6978e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9525e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9755e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5032e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4663e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0403e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7481, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5045e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8475e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6749e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3298e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3461e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1007e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2370e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2280e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1371e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7121e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6537e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2873e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8665e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0169e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6070e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8396e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9513e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1190e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8414e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3651e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2510e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4368e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8613e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9222e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8859e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0968e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3845e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2873e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6372e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9322e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7082e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7432e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7426e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2138e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0139e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3449e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7424e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2494e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8734e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3224e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7099e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5730e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6104e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1130e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8849e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6013e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8371e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4579e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4115e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3972e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9848e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7181e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2631e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4699e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7151e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5689e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1928e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5570e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6739e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0524e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5880e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5658e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9716e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4742e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9443e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2246e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7303e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3427e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1792e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1696e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8072e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4508e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9132e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8916e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1050e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1338e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2328e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3178e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6879e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2885e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7454e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6022e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5871e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6415e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5214e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8059e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8604e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1117e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7627e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3531e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8558e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6667e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6506e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8020e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5429e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5386e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3881e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0684e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4305e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7354e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6327e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7938e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0817e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7687e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1876e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1795e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9128e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2579e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6052e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2458e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0745e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9688e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7024e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4633e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7636e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3155e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7181e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7376e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8976e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2782e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8728e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1190e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4157e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0555e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4560e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4245e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6234e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7493e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0278e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5719e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0806e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7942e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1707e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0897e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9354e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7082e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5256e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4550e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8880e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2631e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7853e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2431e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3427e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6243e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4371e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6416e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6848e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6921e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8120e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1926e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9171e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4002e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4894e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6348e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5144e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8747e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4409e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0339e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0372e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1596e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0118e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8838e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9373e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 17---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7368421052631579, 'agreement': 0.625, 'direct_attack': 0.27906976744186046, 'undercutter_attack': 0.1076923076923077, 'partial': 0.2857142857142857}, 'recall': {'support': 0.8028673835125448, 'agreement': 0.5056179775280899, 'direct_attack': 0.36363636363636365, 'undercutter_attack': 0.08974358974358974, 'partial': 0.21052631578947367}, 'f1': {'support': 0.7684391080617495, 'agreement': 0.5590062111801242, 'direct_attack': 0.31578947368421056, 'undercutter_attack': 0.09790209790209789, 'partial': 0.24242424242424243}, 'support': {'support': 279, 'agreement': 89, 'direct_attack': 33, 'undercutter_attack': 78, 'partial': 19}, 'micro_avg': {'precision': 0.5863453815261044, 'recall': 0.5863453815261044, 'f1': 0.5863453815261044, 'support': None}, 'macro_avg': {'precision': 0.40686369322232235, 'recall': 0.3944783260420124, 'f1': 0.39671222665048494, 'support': None}, 'weighted_avg': {'precision': 0.5707667090814736, 'recall': 0.5863453815261044, 'f1': 0.5759227727274345, 'support': None}}
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2670e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3067e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1683e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1290e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8167e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6152e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9210e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2852e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0157e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5126e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4539e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8366e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8797e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8211e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5156e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8340e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2601e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6781e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6494e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9513e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2966e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6848e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7164e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1489e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5274e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5520e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3479e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3185e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8556e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4046e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7255e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6675e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5901e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3893e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5338e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3479e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8392e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4729e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6721e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7545e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7617e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3388e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1279e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8159e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7493e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2410e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8880e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8998e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9854e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0157e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8674e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8275e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8734e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8695e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3367e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5213e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5940e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1338e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9686e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2380e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7687e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4812e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9854e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3470e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6122e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3237e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2925e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6312e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7848e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5888e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8068e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9819e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9582e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6515e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4539e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4500e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0786e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5888e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2199e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6881e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4197e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6969e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6619e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9353e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8528e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6428e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9967e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3287e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7757e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9202e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8829e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9625e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3137e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2955e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1956e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5758e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5205e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3639e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6576e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5507e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9794e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4002e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1723e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5607e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6377e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5507e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9158e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2579e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3760e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6130e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7877e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0685e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0088e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1459e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1874e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0707e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4093e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0884e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0693e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2519e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7759e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3154e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7968e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3570e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6863e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4178e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8129e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1321e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2743e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4075e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9876e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2840e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2298e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8031e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8062e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6597e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3025e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4115e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2086e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8704e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8275e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5464e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6243e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7034e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3094e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5731e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9231e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9119e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4038e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3094e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7272e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2307e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6780e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0817e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7393e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5196e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5244e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0451e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9132e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6641e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5289e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5651e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5689e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0823e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7051e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1429e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0866e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8868e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9191e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3366e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6053e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2159e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9867e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5062e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6508e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6760e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4841e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4253e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2670e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4638e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5092e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1632e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5528e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7817e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5598e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3972e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4460e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8050e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4426e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5040e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8656e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0702e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2026e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4223e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3793e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5468e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8050e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4063e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1363e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3708e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1109e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5267e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4428e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0828e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3790e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4526e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4850e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1247e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5265e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9885e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5934e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9612e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8211e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4387e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4135e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0767e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9857e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6216e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8304e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2319e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7817e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4690e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0303e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3449e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9552e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3557e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3963e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5598e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8604e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6615e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6195e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8829e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4914e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0066e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6100e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8695e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0905e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5334e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9141e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6013e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1117e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7212e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9885e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5356e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5390e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7829e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3276e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5326e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2099e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4608e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9097e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4802e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6675e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5601e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8779e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3155e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5378e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8526e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4922e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1187e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0853e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6679e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2804e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3743e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5940e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1580e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4814e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7375e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5255e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8172e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2077e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2047e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8976e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5546e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7393e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0566e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1671e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7436e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2731e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8271e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0187e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8492e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2117e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9031e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4054e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3102e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8180e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8976e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8613e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1099e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1117e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9392e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6294e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8340e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2873e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2794e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6809e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5282e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5286e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6005e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5244e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7354e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2312e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7707e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7765e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3738e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1835e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3207e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3015e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1079e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2653e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4699e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0160e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6009e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5416e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2631e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9249e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2679e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8655e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7950e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1710e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3984e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9465e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7735e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0784e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2480e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5577e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9273e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8958e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8431e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5719e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0182e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6282e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0209e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8613e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4296e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3163e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7462e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0654e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1096e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5964e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8586e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4460e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4630e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1186e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9861e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8552e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0430e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1913e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6636e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4992e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7311e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9854e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9119e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7748e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1913e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2276e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7628e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2320e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0278e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8595e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9952e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8061e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7022e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9249e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9997e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4953e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8565e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2912e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9391e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8656e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0897e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3769e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3284e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0118e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8729e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0312e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5507e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1835e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5074e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3682e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2912e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4093e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0784e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5244e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6841e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3950e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 18---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7368421052631579, 'agreement': 0.625, 'direct_attack': 0.2857142857142857, 'undercutter_attack': 0.10606060606060606, 'partial': 0.2857142857142857}, 'recall': {'support': 0.8028673835125448, 'agreement': 0.5056179775280899, 'direct_attack': 0.36363636363636365, 'undercutter_attack': 0.08974358974358974, 'partial': 0.21052631578947367}, 'f1': {'support': 0.7684391080617495, 'agreement': 0.5590062111801242, 'direct_attack': 0.32, 'undercutter_attack': 0.09722222222222222, 'partial': 0.24242424242424243}, 'support': {'support': 279, 'agreement': 89, 'direct_attack': 33, 'undercutter_attack': 78, 'partial': 19}, 'micro_avg': {'precision': 0.5863453815261044, 'recall': 0.5863453815261044, 'f1': 0.5863453815261044, 'support': None}, 'macro_avg': {'precision': 0.40786625655046704, 'recall': 0.3944783260420124, 'f1': 0.39741835677766774, 'support': None}, 'weighted_avg': {'precision': 0.5709514407596209, 'recall': 0.5863453815261044, 'f1': 0.5760952969551267, 'support': None}}
Loss: tensor(3.3397e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2601e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9733e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6791e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0330e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7099e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6537e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8453e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4517e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4802e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2613e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5040e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6213e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0248e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1187e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8072e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3025e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4417e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6052e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1269e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9452e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0291e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7644e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5662e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7577e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8474e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6446e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6948e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0581e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7811e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8950e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5858e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9461e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0091e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1511e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6328e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5501e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9936e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6213e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6788e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7155e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3578e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3228e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6769e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8565e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6417e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7708e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5104e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0473e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5205e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6485e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7666e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3587e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2359e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0430e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8189e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2700e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0763e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1853e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7000e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4480e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2843e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4465e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9858e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4720e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2123e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5577e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0157e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8708e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4495e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1947e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5680e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5010e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3641e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6084e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8029e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6818e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3672e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6961e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0854e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4559e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7133e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2182e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6221e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8495e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0070e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6122e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7608e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2761e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3587e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4616e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9491e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8072e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6584e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7839e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5961e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1671e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2761e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9262e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8616e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5610e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5207e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3655e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2510e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0988e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8189e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1744e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6046e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1126e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4275e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5386e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9331e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2350e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2806e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2946e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9067e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1792e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9945e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9512e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1774e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5252e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1270e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7203e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1239e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3155e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9059e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4266e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2441e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0239e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8159e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8401e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8643e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4011e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4404e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2613e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7795e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3367e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5849e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3518e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0572e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3072e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7406e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8855e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3490e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0059e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2783e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9146e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6175e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7435e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1169e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2583e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4236e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1242e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7142e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0069e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7487e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5477e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1762e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8102e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8351e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9331e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6130e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5365e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6690e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8717e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9080e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0757e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9011e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5580e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6130e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3782e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2289e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1048e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7920e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0512e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5153e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2843e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3003e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3757e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8271e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8637e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2601e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3821e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4526e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7457e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6182e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4892e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7484e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6736e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5166e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5669e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8492e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7795e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3457e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9400e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9918e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1340e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8929e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4357e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6818e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3088e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6930e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6948e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6615e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9724e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9188e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2147e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8232e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6364e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7700e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9291e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5347e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5161e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2380e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4955e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0672e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3669e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5165e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4599e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7557e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0875e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4369e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5183e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6848e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3920e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9945e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3306e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5447e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4063e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1831e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6042e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6182e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5476e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8727e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7341e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2168e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3997e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4681e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8937e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7666e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5858e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2270e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3851e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6022e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1563e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2268e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3106e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4175e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6524e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3784e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5529e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8213e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3397e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1671e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3730e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3306e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6251e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5555e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2164e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2583e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7224e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6143e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9037e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9378e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4677e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8747e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1368e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7432e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9543e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7193e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3197e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3405e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1026e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9430e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9958e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9482e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9149e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8636e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8522e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7847e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2095e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9545e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9552e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1572e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2241e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5494e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3667e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8868e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0854e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7436e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9876e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0763e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1289e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9534e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8885e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1459e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1775e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7908e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3401e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7566e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6588e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3760e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5395e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3427e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1610e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0914e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2822e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2276e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8916e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6978e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4523e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3691e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1822e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4214e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6295e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9284e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4115e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8786e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4677e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8786e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0533e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4426e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1429e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1774e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3003e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4526e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9291e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4863e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8392e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2512e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8798e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4668e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5620e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6084e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9755e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3055e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3518e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9980e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2823e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2155e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0432e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1632e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4387e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6554e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3560e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4668e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7878e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3314e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1831e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7666e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8868e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7566e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2860e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2133e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7726e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9188e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4102e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6031e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1977e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8414e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9923e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3982e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7181e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9815e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1572e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2670e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1148e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1450e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6054e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7778e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3224e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0109e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5750e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1874e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4889e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2825e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7925e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8513e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1247e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2562e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0135e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1459e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0837e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5940e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7819e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8546e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1277e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4154e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5035e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5753e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0239e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7866e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3072e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6113e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3155e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7947e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5144e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5101e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3669e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2224e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5477e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2587e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1844e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2428e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2073e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7544e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7454e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4289e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3405e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4244e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2631e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3721e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6788e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3872e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1866e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6860e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8465e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4556e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8133e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6191e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1683e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2791e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8665e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0239e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8773e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1065e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6342e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6578e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4880e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4123e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6917e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1260e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2934e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6406e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8393e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 19---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7320261437908496, 'agreement': 0.5921052631578947, 'direct_attack': 0.3235294117647059, 'undercutter_attack': 0.08823529411764706, 'partial': 0.2857142857142857}, 'recall': {'support': 0.8028673835125448, 'agreement': 0.5056179775280899, 'direct_attack': 0.3333333333333333, 'undercutter_attack': 0.07692307692307693, 'partial': 0.21052631578947367}, 'f1': {'support': 0.7658119658119658, 'agreement': 0.5454545454545453, 'direct_attack': 0.3283582089552239, 'undercutter_attack': 0.0821917808219178, 'partial': 0.24242424242424243}, 'support': {'support': 279, 'agreement': 89, 'direct_attack': 33, 'undercutter_attack': 78, 'partial': 19}, 'micro_avg': {'precision': 0.5823293172690763, 'recall': 0.5823293172690763, 'f1': 0.5823293172690763, 'support': None}, 'macro_avg': {'precision': 0.4043220797090766, 'recall': 0.38585361741730373, 'f1': 0.39284814869357904, 'support': None}, 'weighted_avg': {'precision': 0.5620884688688411, 'recall': 0.5823293172690763, 'f1': 0.5704012719130233, 'support': None}}
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9430e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6978e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1671e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1935e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7931e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1801e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6013e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3963e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8937e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1338e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4396e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4063e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6818e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9340e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8181e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8371e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3509e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9625e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1156e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4184e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3933e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7960e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5032e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9606e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3408e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5782e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7142e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6911e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9019e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6584e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6485e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1740e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2098e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6870e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1762e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3630e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4759e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5924e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5040e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2285e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6978e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1407e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2315e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9257e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9846e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8465e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0187e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6536e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1679e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7735e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1180e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9028e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3802e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3799e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5641e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8816e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5425e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8946e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5173e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5464e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2921e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8462e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3578e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1804e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7696e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2315e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1580e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2579e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3942e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6212e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2177e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4859e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2333e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3457e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3163e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1498e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1792e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8423e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1853e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8100e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6221e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7696e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2359e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2117e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6348e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8950e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0036e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3609e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6727e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1489e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0226e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4872e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7151e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9342e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2147e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2087e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4905e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5676e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9603e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7787e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4556e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1459e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7281e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6679e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7423e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7393e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3617e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4798e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8250e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9822e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5131e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3185e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8755e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9885e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4275e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6861e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5876e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6213e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9318e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1074e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4650e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7930e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5849e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5183e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8896e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8801e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3678e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6576e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8071e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8029e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0421e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3478e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6778e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3405e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0801e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8250e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5168e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9510e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1643e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2679e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3254e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2337e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7729e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9188e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2592e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9854e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1801e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6039e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3859e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7977e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4429e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2107e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2601e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9512e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5910e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7311e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8643e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0884e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5706e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9309e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6658e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8674e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5940e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7160e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5871e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4842e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4828e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4223e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5849e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1452e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6584e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2860e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1982e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5144e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7917e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0125e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9130e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9149e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5709e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5650e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3137e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9429e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3829e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7129e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0533e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9606e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2709e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2713e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1675e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3245e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9361e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4448e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7402e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5425e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4911e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9089e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8011e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0559e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9582e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1874e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9681e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8757e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9586e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7274e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4248e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2557e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7644e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3639e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2065e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2588e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9176e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6887e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1583e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2611e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8253e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9845e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5918e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9534e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0028e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7129e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1766e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3397e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3669e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7168e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0040e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0157e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5680e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6022e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7021e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0685e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7856e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4344e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4836e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4344e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3267e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7761e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9170e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1987e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8853e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3224e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1641e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9681e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8855e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1180e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6528e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7263e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9088e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7298e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9673e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1580e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6264e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7281e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2947e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0161e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1770e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5979e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8961e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4156e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3027e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8384e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9602e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1813e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6963e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1481e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8431e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9552e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6104e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7913e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8583e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3790e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5823e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8492e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3601e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6355e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7688e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3963e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7817e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8734e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1268e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3457e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0460e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2434e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2770e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0166e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7405e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5840e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3829e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2752e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8615e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4911e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4063e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7432e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3526e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7563e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3842e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3155e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5105e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5888e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3314e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4552e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3826e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2875e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7544e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6100e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4518e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4768e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7177e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6969e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9667e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9309e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1861e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0408e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5224e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6122e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9339e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2318e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3769e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8374e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4601e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8968e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2016e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4054e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4126e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5970e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3347e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0927e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2367e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6130e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9828e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0239e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9499e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8613e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5525e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5235e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7402e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0451e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3009e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2743e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4283e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4893e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7099e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0248e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2860e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7242e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5585e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1239e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2043e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9824e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0390e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6070e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2773e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5646e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9296e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4066e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8515e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6425e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2885e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3115e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3751e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1528e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7462e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4841e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8292e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4911e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6009e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6160e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4547e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2117e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1936e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1169e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1731e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4407e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0330e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9390e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9675e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2895e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5871e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2803e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5123e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2519e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0434e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5144e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9288e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6645e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4357e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5819e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9391e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8531e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8643e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1735e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8742e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8217e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8807e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3980e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0914e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1013e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3528e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3821e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5876e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5407e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5789e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1321e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3784e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6524e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6124e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5921e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3712e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1277e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7172e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4335e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4102e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5378e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3972e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1770e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3176e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0888e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5183e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2125e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3942e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8898e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3306e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0278e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0360e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8500e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4882e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1643e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3436e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8855e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9149e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1465e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7178e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2921e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4154e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3460e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1117e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1013e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5195e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7564e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1157e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0620e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9469e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4862e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1641e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0654e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2709e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5852e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7765e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3028e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8020e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4102e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8384e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7465e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1900e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5343e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3834e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6839e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1178e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4737e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7856e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6871e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6325e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3375e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1268e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6409e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2207e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4802e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3215e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1152e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0347e-05, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 20---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7344262295081967, 'agreement': 0.5921052631578947, 'direct_attack': 0.3055555555555556, 'undercutter_attack': 0.08955223880597014, 'partial': 0.2857142857142857}, 'recall': {'support': 0.8028673835125448, 'agreement': 0.5056179775280899, 'direct_attack': 0.3333333333333333, 'undercutter_attack': 0.07692307692307693, 'partial': 0.21052631578947367}, 'f1': {'support': 0.7671232876712328, 'agreement': 0.5454545454545453, 'direct_attack': 0.31884057971014496, 'undercutter_attack': 0.08275862068965517, 'partial': 0.24242424242424243}, 'support': {'support': 279, 'agreement': 89, 'direct_attack': 33, 'undercutter_attack': 78, 'partial': 19}, 'micro_avg': {'precision': 0.5823293172690763, 'recall': 0.5823293172690763, 'f1': 0.5823293172690763, 'support': None}, 'macro_avg': {'precision': 0.40147071454838057, 'recall': 0.38585361741730373, 'f1': 0.39132025518996416, 'support': None}, 'weighted_avg': {'precision': 0.5624483249851605, 'recall': 0.5823293172690763, 'f1': 0.5705940240080664, 'support': None}}
Loss: tensor(5.4347e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3163e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9418e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6173e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2360e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4102e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3972e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4074e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9876e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0038e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2186e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3218e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5676e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7605e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6831e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9423e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9548e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7153e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4854e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4435e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5131e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6584e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0036e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9893e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2125e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4980e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6100e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7372e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8665e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8682e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4777e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1861e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2672e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2229e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0499e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2943e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7674e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2852e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1178e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9227e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0554e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6774e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5667e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3024e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5023e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6070e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2934e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7947e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6282e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9422e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5775e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2612e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9323e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4707e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4586e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7402e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1792e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7081e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8682e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4426e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6930e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8855e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9582e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5538e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4768e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3124e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9857e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9706e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9594e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0754e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3945e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7746e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9300e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3055e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2691e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6554e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3894e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3823e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0009e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9422e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7384e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5153e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8606e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3700e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1208e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2666e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0196e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3276e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7385e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5589e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4106e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8552e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2079e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3436e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9954e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6372e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4833e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5933e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1186e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9737e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3600e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5585e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0361e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9433e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9393e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7656e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8141e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5473e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3609e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9340e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7757e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2194e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8855e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9885e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4121e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7281e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3441e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1528e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5676e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8280e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3738e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1891e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5477e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9070e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2194e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7034e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2679e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9776e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7617e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4983e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8228e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3827e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9180e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9849e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2125e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5161e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8795e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4771e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8379e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2398e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9271e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3617e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4828e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0520e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9742e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4779e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6879e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0754e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8414e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2467e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9651e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3389e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0438e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7163e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9287e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8976e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0435e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5304e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1195e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0892e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9733e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2640e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4893e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7380e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0097e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2951e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4277e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9033e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5585e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1589e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2320e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1641e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3526e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1528e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0430e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5331e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9612e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1195e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6653e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7129e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7372e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1831e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1899e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5131e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9484e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6584e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4842e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3335e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8230e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6463e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7158e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0187e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1299e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8937e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0953e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9185e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7462e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2055e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9530e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5282e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1520e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1498e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3310e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7440e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7138e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8098e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9158e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7229e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3457e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7380e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2099e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8302e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7607e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9984e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5698e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6403e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9045e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9287e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3708e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9331e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9097e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1139e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3246e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8197e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5558e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7232e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2895e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7973e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1338e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1165e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7516e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0460e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3049e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5244e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3116e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3299e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0845e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7402e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9954e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0581e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7996e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1520e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7878e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7454e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9984e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9281e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0270e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0298e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6727e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9443e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2359e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0542e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1357e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5525e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4066e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4165e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8862e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0226e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4577e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2709e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3382e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9181e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5731e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6033e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3147e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9766e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1217e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1528e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6956e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1217e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7096e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8081e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4500e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4525e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0248e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5862e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3267e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6589e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9660e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0438e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1922e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4176e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2769e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7977e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3760e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4526e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4737e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6699e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2579e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3671e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9706e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8288e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3245e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6818e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7272e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2519e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2043e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8907e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1316e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8125e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1540e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0520e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4547e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9815e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7507e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1770e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3072e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3539e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4751e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6463e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0347e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8988e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1580e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3722e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7129e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3160e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9121e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9126e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7683e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5792e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1529e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4033e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4798e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7030e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2339e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9673e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3524e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5737e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4145e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7465e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6083e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1624e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2056e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5463e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6295e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0135e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3628e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2398e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2731e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9666e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9152e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2099e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0481e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6100e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0797e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9151e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0801e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4620e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0032e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6744e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4556e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4696e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7596e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5123e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3314e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9300e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8825e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1671e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2833e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3539e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9984e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8444e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6638e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7683e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7319e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1373e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8813e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5680e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3693e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9482e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0520e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3548e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7071e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6282e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7735e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8526e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4257e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3421e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2436e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9945e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9197e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1376e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0633e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8301e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1693e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1369e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4566e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9469e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0499e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2752e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7808e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6191e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5643e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0086e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4032e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5464e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6545e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3647e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9772e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7333e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2376e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6584e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5906e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0996e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5092e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5013e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5979e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0620e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7250e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5689e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0430e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0377e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5274e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3185e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5676e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9655e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3329e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9430e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9612e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3094e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5130e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7916e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1922e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0983e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6403e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0724e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2116e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9984e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6854e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7656e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4997e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6108e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8877e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8120e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6463e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2821e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0624e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4054e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9789e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6039e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1498e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3297e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5942e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2937e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5434e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0866e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6143e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3730e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8452e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7983e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9733e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2600e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2782e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4990e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8455e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1286e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5546e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8500e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3617e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1450e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8153e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4728e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6324e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4526e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7851e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1498e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9350e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2340e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9651e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9040e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5428e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5126e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6160e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2722e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9945e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5300e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4980e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7947e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1437e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9452e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7190e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7947e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7777e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4781e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1682e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7549e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5615e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7698e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4247e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5914e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3950e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2155e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6282e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8704e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4950e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4132e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6699e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9264e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2043e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8076e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0611e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2852e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2138e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3068e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6082e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5494e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1211e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8980e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8392e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3618e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2328e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0330e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0460e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6593e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0499e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7257e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7955e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3678e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1671e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2224e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6809e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8885e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0572e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0036e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3150e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7826e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8998e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0049e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)


		-------------RUN 2-----------
			------------EPOCH 1---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.0, 'agreement': 0.0, 'direct_attack': 0.0, 'undercutter_attack': 0.14065934065934066, 'partial': 0.0}, 'recall': {'support': 0.0, 'agreement': 0.0, 'direct_attack': 0.0, 'undercutter_attack': 1.0, 'partial': 0.0}, 'f1': {'support': 0.0, 'agreement': 0.0, 'direct_attack': 0.0, 'undercutter_attack': 0.24662813102119463, 'partial': 0.0}, 'support': {'support': 271, 'agreement': 32, 'direct_attack': 34, 'undercutter_attack': 64, 'partial': 55}, 'micro_avg': {'precision': 0.14035087719298245, 'recall': 0.14035087719298245, 'f1': 0.14035087719298245, 'support': None}, 'macro_avg': {'precision': 0.028131868131868132, 'recall': 0.2, 'f1': 0.04932562620423893, 'support': None}, 'weighted_avg': {'precision': 0.019741661846925006, 'recall': 0.14035087719298245, 'f1': 0.03461447452929047, 'support': None}}
Loss: tensor(2.1120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7915, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8774, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9774, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8962, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6926, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6871, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7569, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6730, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6806, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6957, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9983, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2987, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7374, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4843, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7862, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4868, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9714, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2806, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3761, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5751, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2837, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2751, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2750, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7785, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5719, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9965, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7852, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1730, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7806, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5998, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0738, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3604, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5987, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7481, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5784, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6813, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5757, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5693, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0987, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4374, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4957, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6890, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1740, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3890, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0773, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5885, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0940, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8921, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6801, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7898, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6885, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5900, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8860, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7987, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0831, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5956, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5898, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9740, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9985, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1955, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8616, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3720, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9904, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6898, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6860, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7885, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5720, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7671, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7813, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7714, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3880, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5922, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3862, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5885, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6806, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0769, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6912, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5890, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0683, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2940, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1604, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4374, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3840, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5784, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9553, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3947, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3705, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5921, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6862, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4604, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0740, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4873, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2680, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6632, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9926, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8983, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4754, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1744, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6751, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4998, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9753, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6935, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0784, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2601, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6852, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4985, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5868, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1826, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9754, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8212, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 2---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7378048780487805, 'agreement': 0.23333333333333334, 'direct_attack': 0.10194174757281553, 'undercutter_attack': 0.0, 'partial': 0.2692307692307692}, 'recall': {'support': 0.44649446494464945, 'agreement': 0.4375, 'direct_attack': 0.6176470588235294, 'undercutter_attack': 0.0, 'partial': 0.12727272727272726}, 'f1': {'support': 0.5563218390804597, 'agreement': 0.3043478260869565, 'direct_attack': 0.17500000000000002, 'undercutter_attack': 0.0, 'partial': 0.1728395061728395}, 'support': {'support': 271, 'agreement': 32, 'direct_attack': 34, 'undercutter_attack': 64, 'partial': 55}, 'micro_avg': {'precision': 0.3574561403508772, 'recall': 0.3574561403508772, 'f1': 0.35745614035087725, 'support': None}, 'macro_avg': {'precision': 0.2684621456371397, 'recall': 0.3257828502081812, 'f1': 0.2417018342680511, 'support': None}, 'weighted_avg': {'precision': 0.4949243428575751, 'recall': 0.3574561403508772, 'f1': 0.38587395101994154, 'support': None}}
Loss: tensor(2.0490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5904, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8785, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1693, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2913, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2798, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3794, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1844, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6641, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9374, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9862, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9632, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0935, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2965, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1844, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1985, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0680, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1777, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2843, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3898, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6977, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9997, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(10.1259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3950, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8801, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1873, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2957, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1632, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6860, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9569, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8912, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1956, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3553, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3511, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3847, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0840, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3998, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2757, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6801, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3926, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8900, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5880, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6921, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4427, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0481, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2847, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9761, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1843, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2632, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5817, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3987, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2971, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5890, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6783, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3794, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9738, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1791, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6806, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5801, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7720, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2860, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7983, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0906, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0713, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3904, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8826, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7750, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1801, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7806, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6956, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3719, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2783, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8798, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6904, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1783, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6719, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2798, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5929, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0604, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0683, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0761, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0985, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1885, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0929, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4761, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5797, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5844, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1922, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9898, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9701, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1904, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2994, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2955, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6739, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3785, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2826, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1929, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7985, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0852, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7837, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0750, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8842, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 3---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6645962732919255, 'agreement': 0.2916666666666667, 'direct_attack': 0.08791208791208792, 'undercutter_attack': 0.14935064935064934, 'partial': 0.2692307692307692}, 'recall': {'support': 0.3948339483394834, 'agreement': 0.21875, 'direct_attack': 0.23529411764705882, 'undercutter_attack': 0.359375, 'partial': 0.12727272727272726}, 'f1': {'support': 0.49537037037037035, 'agreement': 0.25, 'direct_attack': 0.128, 'undercutter_attack': 0.2110091743119266, 'partial': 0.1728395061728395}, 'support': {'support': 271, 'agreement': 32, 'direct_attack': 34, 'undercutter_attack': 64, 'partial': 55}, 'micro_avg': {'precision': 0.3333333333333333, 'recall': 0.3333333333333333, 'f1': 0.3333333333333333, 'support': None}, 'macro_avg': {'precision': 0.29255128929041974, 'recall': 0.2671051586518539, 'f1': 0.25144381017102735, 'support': None}, 'weighted_avg': {'precision': 0.4754255882688377, 'recall': 0.3333333333333333, 'f1': 0.37194765431105226, 'support': None}}
Loss: tensor(0.6368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1965, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1997, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8427, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4977, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2481, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3940, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0972, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1604, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7904, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0950, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3754, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1671, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0654, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3774, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2873, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2906, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0569, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1791, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6955, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3784, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0560, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0694, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4654, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6660, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0662, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8921, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0797, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1926, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0713, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9817, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0374, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3957, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2641, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0987, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9972, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3739, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2511, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0983, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9796, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1796, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0798, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2616, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5720, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2719, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0921, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8671, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3773, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5652, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0847, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4635, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6862, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2740, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0871, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2935, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5601, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1831, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0880, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0922, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0694, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2784, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0719, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0751, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1860, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2791, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0904, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0935, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3701, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9773, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6898, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5783, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0769, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0994, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1860, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1885, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1847, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6847, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6654, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1765, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6955, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8719, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4890, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1801, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0862, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0977, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3798, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1751, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1738, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9906, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0604, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9761, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2922, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0739, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1815, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 4---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6950354609929078, 'agreement': 0.2727272727272727, 'direct_attack': 0.375, 'undercutter_attack': 0.19327731092436976, 'partial': 0.5}, 'recall': {'support': 0.7232472324723247, 'agreement': 0.28125, 'direct_attack': 0.17647058823529413, 'undercutter_attack': 0.359375, 'partial': 0.05454545454545454}, 'f1': {'support': 0.7088607594936709, 'agreement': 0.2769230769230769, 'direct_attack': 0.24, 'undercutter_attack': 0.25136612021857924, 'partial': 0.09836065573770492}, 'support': {'support': 271, 'agreement': 32, 'direct_attack': 34, 'undercutter_attack': 64, 'partial': 55}, 'micro_avg': {'precision': 0.5197368421052632, 'recall': 0.5197368421052632, 'f1': 0.5197368421052632, 'support': None}, 'macro_avg': {'precision': 0.40720800892891, 'recall': 0.31897765505061465, 'f1': 0.31510212247460634, 'support': None}, 'weighted_avg': {'precision': 0.5475912950778737, 'recall': 0.5197368421052632, 'f1': 0.5057457720260661, 'support': None}}
Loss: tensor(0.3898, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4935, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0797, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5616, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6913, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1844, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0900, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0903, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2962, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0730, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0774, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0773, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0906, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2957, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0680, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0604, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0750, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0965, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1947, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7654, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0798, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1511, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0950, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0794, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0774, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3683, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0713, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0862, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0713, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0813, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0632, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0826, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0560, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0900, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0761, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0635, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9740, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2915, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6652, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5601, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0987, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0701, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0978, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0569, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1714, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9950, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7987, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8604, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9985, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5903, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1985, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0806, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0915, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 5---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6426592797783933, 'agreement': 0.4444444444444444, 'direct_attack': 0.3181818181818182, 'undercutter_attack': 0.16129032258064516, 'partial': 0.3333333333333333}, 'recall': {'support': 0.8560885608856088, 'agreement': 0.5, 'direct_attack': 0.20588235294117646, 'undercutter_attack': 0.078125, 'partial': 0.03636363636363636}, 'f1': {'support': 0.7341772151898733, 'agreement': 0.47058823529411764, 'direct_attack': 0.25, 'undercutter_attack': 0.10526315789473684, 'partial': 0.06557377049180327}, 'support': {'support': 271, 'agreement': 32, 'direct_attack': 34, 'undercutter_attack': 64, 'partial': 55}, 'micro_avg': {'precision': 0.5745614035087719, 'recall': 0.5745614035087719, 'f1': 0.5745614035087719, 'support': None}, 'macro_avg': {'precision': 0.37998183966372684, 'recall': 0.33529191003808434, 'f1': 0.32512047577410624, 'support': None}, 'weighted_avg': {'precision': 0.49968636587465626, 'recall': 0.5745614035087719, 'f1': 0.5106672112460082, 'support': None}}
Loss: tensor(0.0424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0921, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0553, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1777, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5754, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0641, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0972, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7874, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6955, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0635, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0757, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0773, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0826, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1813, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8885, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 6---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6567164179104478, 'agreement': 0.38235294117647056, 'direct_attack': 0.2962962962962963, 'undercutter_attack': 0.14, 'partial': 0.5}, 'recall': {'support': 0.8118081180811808, 'agreement': 0.40625, 'direct_attack': 0.23529411764705882, 'undercutter_attack': 0.109375, 'partial': 0.09090909090909091}, 'f1': {'support': 0.7260726072607261, 'agreement': 0.393939393939394, 'direct_attack': 0.2622950819672131, 'undercutter_attack': 0.12280701754385966, 'partial': 0.15384615384615385}, 'support': {'support': 271, 'agreement': 32, 'direct_attack': 34, 'undercutter_attack': 64, 'partial': 55}, 'micro_avg': {'precision': 0.5548245614035088, 'recall': 0.5548245614035088, 'f1': 0.5548245614035088, 'support': None}, 'macro_avg': {'precision': 0.395073131076643, 'recall': 0.3307272653274661, 'f1': 0.33179205091146924, 'support': None}, 'weighted_avg': {'precision': 0.5191656084330099, 'recall': 0.5548245614035088, 'f1': 0.5144977139143598, 'support': None}}
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3957, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0596e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0860e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9518e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5692e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6288e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3856e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9062e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5774e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2301e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7902e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4774e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5520e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5309e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0494e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0738, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2383e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0427, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0632, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0720, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 7---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6785714285714286, 'agreement': 0.35185185185185186, 'direct_attack': 0.4, 'undercutter_attack': 0.2, 'partial': 0.5555555555555556}, 'recall': {'support': 0.7712177121771218, 'agreement': 0.59375, 'direct_attack': 0.23529411764705882, 'undercutter_attack': 0.203125, 'partial': 0.09090909090909091}, 'f1': {'support': 0.7219343696027634, 'agreement': 0.4418604651162791, 'direct_attack': 0.29629629629629634, 'undercutter_attack': 0.20155038759689922, 'partial': 0.15625}, 'support': {'support': 271, 'agreement': 32, 'direct_attack': 34, 'undercutter_attack': 64, 'partial': 55}, 'micro_avg': {'precision': 0.5570175438596491, 'recall': 0.5570175438596491, 'f1': 0.5570175438596491, 'support': None}, 'macro_avg': {'precision': 0.4371957671957672, 'recall': 0.3788591841466543, 'f1': 0.3635783037224476, 'support': None}, 'weighted_avg': {'precision': 0.5528677016615614, 'recall': 0.5570175438596491, 'f1': 0.5292780656279504, 'support': None}}
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8789e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8729e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0415e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7548e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9022e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8973e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8223e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2049e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3533e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8425e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5037e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6337e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3412e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1435e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1878e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9658e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6175e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0212e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9837e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9849e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2837e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5995e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1293e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9173e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1108e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9073e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5924e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8153e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9679e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8398e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 8---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6782334384858044, 'agreement': 0.391304347826087, 'direct_attack': 0.3333333333333333, 'undercutter_attack': 0.19047619047619047, 'partial': 0.5555555555555556}, 'recall': {'support': 0.7933579335793358, 'agreement': 0.5625, 'direct_attack': 0.20588235294117646, 'undercutter_attack': 0.1875, 'partial': 0.09090909090909091}, 'f1': {'support': 0.7312925170068029, 'agreement': 0.46153846153846156, 'direct_attack': 0.2545454545454545, 'undercutter_attack': 0.1889763779527559, 'partial': 0.15625}, 'support': {'support': 271, 'agreement': 32, 'direct_attack': 34, 'undercutter_attack': 64, 'partial': 55}, 'micro_avg': {'precision': 0.5635964912280702, 'recall': 0.5635964912280702, 'f1': 0.5635964912280702, 'support': None}, 'macro_avg': {'precision': 0.42978057313539414, 'recall': 0.36802987548592064, 'f1': 0.358520562208695, 'support': None}, 'weighted_avg': {'precision': 0.5491279957005545, 'recall': 0.5635964912280702, 'f1': 0.5313427335999916, 'support': None}}
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9101e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3130e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6913e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7678e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2221e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2230e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7579e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4611e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3826e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8384e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7760e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8456e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3512e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8849e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2261e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8154e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7073e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1989e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7790e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3613e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7951e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8909e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0343e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1654e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7519e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8014e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0715e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2453e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6105e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7962e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8656e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7611e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2328e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0334e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6640e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0412e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0797e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6167e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6872e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6306e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4360e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3400e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7630e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6267e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2119e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0748e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2412e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2754e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1913, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1676e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7093e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5187e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4128e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4692e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5429e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1847e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3397e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2994e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4278e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3008e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6367e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5064e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6186e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8286e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9253e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1030e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6567e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3915e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 9---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6793650793650794, 'agreement': 0.38636363636363635, 'direct_attack': 0.3125, 'undercutter_attack': 0.17857142857142858, 'partial': 0.5555555555555556}, 'recall': {'support': 0.7896678966789668, 'agreement': 0.53125, 'direct_attack': 0.29411764705882354, 'undercutter_attack': 0.15625, 'partial': 0.09090909090909091}, 'f1': {'support': 0.7303754266211605, 'agreement': 0.4473684210526316, 'direct_attack': 0.30303030303030304, 'undercutter_attack': 0.16666666666666666, 'partial': 0.15625}, 'support': {'support': 271, 'agreement': 32, 'direct_attack': 34, 'undercutter_attack': 64, 'partial': 55}, 'micro_avg': {'precision': 0.5614035087719298, 'recall': 0.5614035087719298, 'f1': 0.5614035087719298, 'support': None}, 'macro_avg': {'precision': 0.42247113997114, 'recall': 0.37243892692937625, 'f1': 0.36073816347415233, 'support': None}, 'weighted_avg': {'precision': 0.5462296049467102, 'recall': 0.5614035087719298, 'f1': 0.5302872303897274, 'support': None}}
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6258e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9011e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3947e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6236e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8777e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7973e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5791e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8598e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7821e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1887e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8850e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8738e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8283e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3288e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8586e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0648e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4015e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6237e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7869e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3501e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9647e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7224e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3570e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7183e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6014e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1262e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2867e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2592e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9173e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0464e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2865e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0473e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0070e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6234e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2998e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3025e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1041e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6771e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6437e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0433e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7023e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0624e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6046e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8801e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4218e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8799e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8647e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2461e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8031e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0574e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4651e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7072e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2089e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6065e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9306e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8912e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1420e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8821e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4371e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8729e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7326e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9746e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5994e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8498e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1634e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6309e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0455e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9253e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2474e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0373e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1583e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5083e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7053e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3996e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9908e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8002e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0647e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0775e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3794e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7748e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3158e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0818e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0193e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4048e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3370e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4359e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8971e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7375e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3845e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5037e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5610e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2916e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2794e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5329e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7718e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7627e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8457e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4087e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4978, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2146e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2431e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4581e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4651e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8042e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1573e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8263e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4024e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0524e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9959e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1250e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6216e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0151e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1943e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2471e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8103e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7242e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0112e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0079e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9201e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5894e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3448e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 10---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6697819314641744, 'agreement': 0.391304347826087, 'direct_attack': 0.3, 'undercutter_attack': 0.2, 'partial': 0.5555555555555556}, 'recall': {'support': 0.7933579335793358, 'agreement': 0.5625, 'direct_attack': 0.17647058823529413, 'undercutter_attack': 0.1875, 'partial': 0.09090909090909091}, 'f1': {'support': 0.7263513513513513, 'agreement': 0.46153846153846156, 'direct_attack': 0.22222222222222224, 'undercutter_attack': 0.19354838709677422, 'partial': 0.15625}, 'support': {'support': 271, 'agreement': 32, 'direct_attack': 34, 'undercutter_attack': 64, 'partial': 55}, 'micro_avg': {'precision': 0.5614035087719298, 'recall': 0.5614035087719298, 'f1': 0.5614035087719298, 'support': None}, 'macro_avg': {'precision': 0.42332836696916337, 'recall': 0.3621475225447442, 'f1': 0.35198208444176193, 'support': None}, 'weighted_avg': {'precision': 0.5429565748087315, 'recall': 0.5614035087719298, 'f1': 0.5266378274456054, 'support': None}}
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1382e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9394e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2059e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4592e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0676e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8114e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5368e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5085e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9676e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1038e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1917e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6347e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0303e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4327e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8123e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4169e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8010e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8971e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1117e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7164e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1735e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5456e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2026e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0717e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1261e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8326e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1018e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5934e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8323e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7072e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9719e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8317e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7709e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1675e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3854e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4772e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6779e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6903e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5337e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9162e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4136e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1039e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6727e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0524e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4681e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8798e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6870e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1807e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8626e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7518e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4672e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1453e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6046e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3539e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6618e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2700e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9149e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4084e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4033e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4408e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0141e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4374e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9210e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6640e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2907e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1684e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8392e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1402e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3755e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9838e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8840e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8102e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6152e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8511, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9837e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4147e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5812e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1071e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0129e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3130e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3107e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5810e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1575e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5912e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2077e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4593e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9786e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4348e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2207e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3381e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1277e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8839e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5471e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5358e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8665e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3821e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9768e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0572e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1130e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5540e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3410e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9634e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3251e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0018e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4209e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8525e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3623e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9304e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2413e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5819e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7315e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3661e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1320e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6658e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1614e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1247e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4511e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5062e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0526e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7537e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1693e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5892e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8989e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2351e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3077e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5477e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3037e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8004e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8885e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5187e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6521e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5771e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1947e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5561e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2816e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8514e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8579e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0875e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9528e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4538e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0000e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2004e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4197e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1917e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6569e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4145e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0373e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8255e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1977e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1684e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6143e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7064e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5801e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 11---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.678343949044586, 'agreement': 0.38461538461538464, 'direct_attack': 0.4444444444444444, 'undercutter_attack': 0.20634920634920634, 'partial': 0.5555555555555556}, 'recall': {'support': 0.7859778597785978, 'agreement': 0.625, 'direct_attack': 0.23529411764705882, 'undercutter_attack': 0.203125, 'partial': 0.09090909090909091}, 'f1': {'support': 0.7282051282051282, 'agreement': 0.4761904761904762, 'direct_attack': 0.30769230769230765, 'undercutter_attack': 0.2047244094488189, 'partial': 0.15625}, 'support': {'support': 271, 'agreement': 32, 'direct_attack': 34, 'undercutter_attack': 64, 'partial': 55}, 'micro_avg': {'precision': 0.5679824561403509, 'recall': 0.5679824561403509, 'f1': 0.5679824561403509, 'support': None}, 'macro_avg': {'precision': 0.45386170800183534, 'recall': 0.3880612136669495, 'f1': 0.3746124643073462, 'support': None}, 'weighted_avg': {'precision': 0.5592366630960329, 'recall': 0.5679824561403509, 'f1': 0.5367090694033945, 'support': None}}
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0503e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3912e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4570e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8071e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3954e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9454e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8153e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2683e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0110e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7901e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1655e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4329e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2007e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4099e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3185e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0905e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7872e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4015e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4668e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4126e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0139e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0745e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4620e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9575e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2531e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6095e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6589e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6137e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6467e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8427e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8695e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3503e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8552e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1129e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6356e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1853e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3410e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6285e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0544e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9694e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8288e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5217e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7072e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5659e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0715e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6419e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6243e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1858e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7973e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3449e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7516e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7051e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5187e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6227e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4148e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8083e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1162e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9585e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9301e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8646e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6446e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8435e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0103e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2946e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7588e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1461e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0291e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0291e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2147e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7627e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4630e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8877e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9252e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1885e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7687e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5174e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6839e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9699e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5347e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3721e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8296e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5831e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6727e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7617e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4623e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7878e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8090e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3578e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0848e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4123e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7959e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3419e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1687e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3509e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3914e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0402e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4471e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8838e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2238e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0654e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6848e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0616e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4781e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8907e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1917e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7194e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0161e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5763e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4289e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2129e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0542e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4759e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9080e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2734e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2873e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2440e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4542e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1987e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1368e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7741e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0483e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9455e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5902e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8366e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9385e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3652e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5235e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4360e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1065e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2268e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0646e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0230e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1444e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3169e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2954e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0382e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5983e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0315e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2309e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8720e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2761e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0828e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4914e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9565e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3875e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2149e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6933e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6982e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3591e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9766e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3733e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1644e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7990e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8695e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3673e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2735e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8659e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7721e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6921e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5831e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5760e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8529e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5861e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2246e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1997e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3815e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3993e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3367e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5367e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1341e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3327e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7942e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4590e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3230e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3873e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9032e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5286e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5541e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1864e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0090e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0303e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1390e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8083e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2180e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1997e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7496e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1753e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4720e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7759e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0614e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0976e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1525e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8596e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8447e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3669e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4660e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 12---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6891025641025641, 'agreement': 0.3829787234042553, 'direct_attack': 0.38095238095238093, 'undercutter_attack': 0.208955223880597, 'partial': 0.5555555555555556}, 'recall': {'support': 0.7933579335793358, 'agreement': 0.5625, 'direct_attack': 0.23529411764705882, 'undercutter_attack': 0.21875, 'partial': 0.09090909090909091}, 'f1': {'support': 0.7375643224699828, 'agreement': 0.45569620253164556, 'direct_attack': 0.29090909090909084, 'undercutter_attack': 0.21374045801526717, 'partial': 0.15625}, 'support': {'support': 271, 'agreement': 32, 'direct_attack': 34, 'undercutter_attack': 64, 'partial': 55}, 'micro_avg': {'precision': 0.5701754385964912, 'recall': 0.5701754385964912, 'f1': 0.5701754385964912, 'support': None}, 'macro_avg': {'precision': 0.4435088895790706, 'recall': 0.3801622284270971, 'f1': 0.37083201478519723, 'support': None}, 'weighted_avg': {'precision': 0.5611473352127758, 'recall': 0.5701754385964912, 'f1': 0.5408470576190003, 'support': None}}
Loss: tensor(7.5145e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9443e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6358e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3885e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9028e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8172e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2207e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6818e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8704e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1070e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5489e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6225e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7173e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9101e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8435e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6879e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7617e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1615e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6545e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7901e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5296e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0170e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1714e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3429e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3431e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2340e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1432e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4117e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3911e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6648e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0718e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7153e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7908e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0966e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3017e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3236e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6554e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4206e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2585e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9928e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7929e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9400e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9028e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7345e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1887e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3440e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0110e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8547e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5276e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9365e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5494e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4360e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1225e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5529e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6922e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1776e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2976e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8807e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7644e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1583e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5489e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0302e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4369e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1571e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9179e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7811e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9370e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7984e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3055e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5287e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5226e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2137e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8989e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9312e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7397e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5455e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6636e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0139e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3600e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6675e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0191e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2916e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5349e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0261e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2268e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5125e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2108e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3751e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8674e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0978e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5973e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0818e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3548e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3738e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8565e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7729e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7838e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3563e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3873e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5087e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1333e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3661e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3842e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3660e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8513e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8850e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0877e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8717e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0269e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5287e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3724e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2479e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4116e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6752e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1502e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7427e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3681e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3924e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7393e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7409e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8172e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8613e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1502e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5652e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7644e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0644e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2712e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1039e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7717e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9315e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3220e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5682e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4296e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6579e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7084e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7153e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6052e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5087e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0875e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2449e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0465e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2462e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4054e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1956e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5282e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5577e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6409e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2004e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1065e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5166e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5319e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9778e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8320e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6325e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9928e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5943e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4811e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0695e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3155e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5801e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9958e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6706e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2127e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7250e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9737e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2017e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6991e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8344e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7436e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7456e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5256e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1554e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5244e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7031e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7035e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7233e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9183e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9860e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8353e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4993e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3742e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4442e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1372e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1723e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8202e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3812e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9091e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7272e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6521e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5744e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1926e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6014e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6446e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9171e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1593e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7281e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8939e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7599e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5430e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1260e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6419e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2925e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6348e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4045e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6215e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7726e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8185e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4911e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5094e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0695e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1916e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7000e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4629e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5538e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9725e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5092e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2583e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4305e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1320e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4772e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6334e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2159e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8416e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2891e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3288e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2679e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7181e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4335e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2670e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3693e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 13---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6739811912225705, 'agreement': 0.4090909090909091, 'direct_attack': 0.36363636363636365, 'undercutter_attack': 0.20967741935483872, 'partial': 0.5555555555555556}, 'recall': {'support': 0.7933579335793358, 'agreement': 0.5625, 'direct_attack': 0.23529411764705882, 'undercutter_attack': 0.203125, 'partial': 0.09090909090909091}, 'f1': {'support': 0.7288135593220338, 'agreement': 0.47368421052631576, 'direct_attack': 0.2857142857142857, 'undercutter_attack': 0.20634920634920634, 'partial': 0.15625}, 'support': {'support': 271, 'agreement': 32, 'direct_attack': 34, 'undercutter_attack': 64, 'partial': 55}, 'micro_avg': {'precision': 0.5679824561403509, 'recall': 0.5679824561403509, 'f1': 0.5679824561403509, 'support': None}, 'macro_avg': {'precision': 0.4423882877720475, 'recall': 0.37703722842709714, 'f1': 0.37016225238236833, 'support': None}, 'weighted_avg': {'precision': 0.552803418136244, 'recall': 0.5679824561403509, 'f1': 0.5354841101617286, 'support': None}}
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5329e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2765e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3427e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0816e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6328e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0435e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0218e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5650e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2735e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9612e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1277e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9331e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3520e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9504e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2462e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0978e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4633e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3481e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5447e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1437e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9733e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8951e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9612e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7052e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7368e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3099e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1489e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2692e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6115e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2237e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0364e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2246e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7408e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8859e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2268e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9043e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3238e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2795e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1359e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3345e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3064e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6328e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0218e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8433e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9867e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2873e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6085e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9785e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7469e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2904e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8586e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5767e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8888e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9058e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6549e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9162e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4599e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0937e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7064e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6403e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0424e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7003e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8072e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1905e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3813e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9694e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1289e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4366e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9179e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6941e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0823e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1035e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8262e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2871, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3660e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9436e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7397e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3945e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9050e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3712e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5226e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0778e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9768e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9878e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9658e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2761e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6752e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1057e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1471e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3193e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7568e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6446e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2320e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7487e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2168e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4007e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2481e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7627e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8453e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5940e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1603e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8930e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9312e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2988e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4071e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4465e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3224e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6394e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2943e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2480e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9153e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5879e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1320e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3331e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9309e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1535e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4673e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8556e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9766e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3745e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4768e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8847e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8678e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7819e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1026e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0815e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2570e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9352e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9582e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8907e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7869e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8001e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2865e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9019e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4902e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1459e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8507e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7895e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7090e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6752e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8957e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4833e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5870e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8397e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2988e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3297e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6070e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7886e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1856e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6909e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2510e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4456e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4024e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2186e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9737e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7203e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9846e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2040e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0914e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4054e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7357e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2428e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5235e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1493e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6103e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7211e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1926e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8183e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7908e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1995e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4088e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7103e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5425e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2783e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1552e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0454e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2359e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9464e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3557e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8825e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2207e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9174e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3621e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1371e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9003e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6903e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5607e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6658e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4335e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5609e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2462e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4517e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5017e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5676e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0281e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9958e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4041e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7950e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0533e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0998e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0675e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1162e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4327e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5161e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6909e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1604e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9534e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2017e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1775e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4123e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1524e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2964e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9035e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7555e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8011e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4317e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0490e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3986e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2276e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0109e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3470e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6921e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1238e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8517e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2016e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2964e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5516e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9997e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3358e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6237e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7129e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8505e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6788e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1208e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8734e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0978e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1619e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5316e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5244e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2549e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8513e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5407e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7531e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4919e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8365e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7151e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0611e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0533e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6769e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1431e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6558e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2229e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7396e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1865e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3783e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8345e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0575e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7003e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3790e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5222e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1332e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4643e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1922e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1916e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5598e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9452e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4902e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9262e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9455e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3261e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5356e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1156e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6770e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1410e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2140e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4851e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9110e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8061e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5095e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3522e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5881e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5434e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7156e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8758e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3854e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3844e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0757e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7142e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4309e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1208e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0987e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4063e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3593e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1917e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7974e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0878e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2186e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5278e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3842e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4517e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3512e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6105e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 14---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6893203883495146, 'agreement': 0.375, 'direct_attack': 0.38095238095238093, 'undercutter_attack': 0.21739130434782608, 'partial': 0.5555555555555556}, 'recall': {'support': 0.7859778597785978, 'agreement': 0.5625, 'direct_attack': 0.23529411764705882, 'undercutter_attack': 0.234375, 'partial': 0.09090909090909091}, 'f1': {'support': 0.7344827586206898, 'agreement': 0.45, 'direct_attack': 0.29090909090909084, 'undercutter_attack': 0.2255639097744361, 'partial': 0.15625}, 'support': {'support': 271, 'agreement': 32, 'direct_attack': 34, 'undercutter_attack': 64, 'partial': 55}, 'micro_avg': {'precision': 0.5679824561403509, 'recall': 0.5679824561403509, 'f1': 0.5679824561403509, 'support': None}, 'macro_avg': {'precision': 0.4436439258410555, 'recall': 0.3818112136669495, 'f1': 0.37144115186084337, 'support': None}, 'weighted_avg': {'precision': 0.5619008886599032, 'recall': 0.5679824561403509, 'f1': 0.5402753879444735, 'support': None}}
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1726e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2065e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9394e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8678e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6840e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0036e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8081e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2967e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4668e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2480e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6800e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7094e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9554e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6455e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8020e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3799e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9021e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2751e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0572e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6355e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6152e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2955e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9755e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0856e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9352e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1502e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5092e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3812e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0939e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3542e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6679e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4478e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1825e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2216e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7529e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5728e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0036e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9612e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7765e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1675e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8324e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6620e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0362e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3046e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4577e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9361e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1169e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3539e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5408e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6576e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7667e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1132e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5706e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7627e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2293e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2086e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5681e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9886e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9161e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9694e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4632e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2554e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0190e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5368e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4671e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9664e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6618e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6519e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6739e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7618e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0278e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3829e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7636e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4984e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1878e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2714e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4690e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1641e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7363e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3479e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0979e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0494e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1381e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1138e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8516e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2289e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3772e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7834e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6419e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2180e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1610e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9443e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4994e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8233e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4955e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9303e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4517e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3784e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0987e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5245e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1320e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2064e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6878e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6809e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6367e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7983e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1563e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1459e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9541e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8537e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1156e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3587e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6312e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2047e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9625e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0896e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6709e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6606e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6545e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2700e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5568e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8969e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5931e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0441e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9252e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2065e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4175e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9079e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4351e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4478e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2177e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0293e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1523e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7660e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5274e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0757e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2068e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3102e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6127e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9124e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5395e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4066e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5274e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2229e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1535e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3267e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0796e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9270e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2141e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6266e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6912e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1532e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8132e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0273e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8954e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4307e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7094e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5043e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3125e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0451e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9158e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0196e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1947e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7072e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4106e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7778e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9537e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9340e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2540e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3133e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8555e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8365e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9845e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8371e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1467e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8089e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5010e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7575e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9293e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2307e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1156e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4435e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9002e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2519e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3348e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9919e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9554e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0936e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1935e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5507e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9796e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6325e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9243e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3284e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7253e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7911e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7163e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8522e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6476e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5892e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6243e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2967e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8980e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6939e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1804e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4396e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1299e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2194e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7272e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5347e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4214e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1151e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1816e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1822e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0418e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1786e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8163e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2803e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1934e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9627e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9309e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1858e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6034e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7856e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6455e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3179e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7176e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2830e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2846e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7136e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3855e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7133e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1736e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2065e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5477e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8656e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4458e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0160e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2709e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3401e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8768e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8072e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3033e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2884e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6031e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4084e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2376e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8535e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6930e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7475e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7605e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3933e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2915e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3457e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8474e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5359e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1896e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1904e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6328e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2059e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1686e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7021e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8172e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7826e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8201e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8558e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9770e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8880e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4923e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7938e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4465e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9383e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9080e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5166e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1610e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7713e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7047e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8828e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9612e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3072e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8456e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7372e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0402e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7341e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1977e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7212e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8029e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5559e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1256e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7514e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2722e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8673e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8708e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8250e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2812e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0914e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5639e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6697e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0363e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5925e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6152e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7332e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1290e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4789e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5849e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7386e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6930e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6204e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5991e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9436e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5601e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6658e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2428e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9727e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7627e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7587e-05, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 15---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6847133757961783, 'agreement': 0.3829787234042553, 'direct_attack': 0.38095238095238093, 'undercutter_attack': 0.2153846153846154, 'partial': 0.5555555555555556}, 'recall': {'support': 0.7933579335793358, 'agreement': 0.5625, 'direct_attack': 0.23529411764705882, 'undercutter_attack': 0.21875, 'partial': 0.09090909090909091}, 'f1': {'support': 0.7350427350427351, 'agreement': 0.45569620253164556, 'direct_attack': 0.29090909090909084, 'undercutter_attack': 0.21705426356589147, 'partial': 0.15625}, 'support': {'support': 271, 'agreement': 32, 'direct_attack': 34, 'undercutter_attack': 64, 'partial': 55}, 'micro_avg': {'precision': 0.5701754385964912, 'recall': 0.5701754385964912, 'f1': 0.5701754385964912, 'support': None}, 'macro_avg': {'precision': 0.4439169302185972, 'recall': 0.3801622284270971, 'f1': 0.37099045840987255, 'support': None}, 'weighted_avg': {'precision': 0.5594412190400272, 'recall': 0.5701754385964912, 'f1': 0.5398135781507017, 'support': None}}
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8216e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7959e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3185e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3412e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8877e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0424e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3085e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8102e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0796e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1035e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4690e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4046e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3669e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0886e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0097e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1913e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1563e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4542e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4828e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0014e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6653e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9725e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4136e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9715e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6900e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5204e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3551e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4720e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6968e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4811e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7883e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2285e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8768e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6950e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4841e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8946e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2643e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9897e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0218e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5398e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0845e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9287e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5810e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6163e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1562e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9366e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1087e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2298e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1420e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8899e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8226e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0969e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7052e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9331e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8885e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9059e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0715e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2601e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3833e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8855e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8362e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2618e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7597e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8887e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6031e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9524e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3702e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2168e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0551e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1762e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1907e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6076e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4430e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7771e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4266e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2460e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7999e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3470e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8643e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4499e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1565e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7091e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0696e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0482e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0161e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7253e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3859e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7959e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8483e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7317e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9776e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9382e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9677e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0058e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6161e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9667e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6616e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5767e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8171e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2103e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9876e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1499e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7493e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6194e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6978e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4551e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7341e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6952e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8505e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3279e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3924e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2125e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3954e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1913e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6416e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3561e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3560e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8068e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2986e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7718e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6779e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8280e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5546e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9213e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5510e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9361e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4162e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6554e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4448e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4208e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8596e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0287e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7319e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5758e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7999e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0140e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2246e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3349e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9849e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2201e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8816e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0226e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9970e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6830e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3478e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5023e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5186e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9923e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1489e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3581e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4941e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4367e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6596e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7233e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3276e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1896e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6121e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9136e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2664e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5555e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3224e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5720e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7038e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2557e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4962e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2034e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5537e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9645e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0009e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2471e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3904e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2761e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2742e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2034e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0926e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5587e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3609e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9400e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8129e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5092e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2857e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9461e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7367e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8787e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9506e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2289e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1550e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1713e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9514e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5041e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4744e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0745e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6312e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2916e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4157e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0200e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3240e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2860e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3133e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1117e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4256e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2362e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5590e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5098e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9504e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6085e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2783e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4456e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1177e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9716e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2871e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7699e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2834e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5164e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9893e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6082e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9767e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6891e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1087e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0218e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1407e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4984e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1109e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0173e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8901e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4114e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1374e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2631e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7847e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2539e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6767e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8816e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5827e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2683e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4811e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7523e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7402e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0866e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4971e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9058e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7523e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6670e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7569e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3792e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8535e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8908e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4811e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3994e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7947e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7436e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8524e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1252e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1558e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4915e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3581e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5797e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8885e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0127e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3439e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9856e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1452e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8710e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3591e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0278e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3950e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6355e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9128e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5953e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5888e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9361e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8226e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6619e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9889e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4223e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0351e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8314e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9061e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0811e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8794e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5368e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7749e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3790e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9586e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4630e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8010e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9331e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1126e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8409e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3198e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7254e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0105e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2571e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0391e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4798e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2728e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3413e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1861e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8916e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8120e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2028e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2761e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0654e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3361e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1368e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1035e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8531e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6261e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6618e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5177e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6204e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3033e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1247e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8656e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3950e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2337e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3197e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5477e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2700e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8635e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5649e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1619e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8771e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2903e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6519e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2125e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1437e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8232e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5789e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6645e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0555e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9491e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2700e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4668e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4570e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1351e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0818e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9424e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7777e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4205e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7859e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1096e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6606e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3647e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1835e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2866e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0347e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4266e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1976e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1955e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1552e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4487e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9158e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6358e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0888e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2002e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6254e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1498e-05, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 16---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6869009584664537, 'agreement': 0.3829787234042553, 'direct_attack': 0.38095238095238093, 'undercutter_attack': 0.21212121212121213, 'partial': 0.5555555555555556}, 'recall': {'support': 0.7933579335793358, 'agreement': 0.5625, 'direct_attack': 0.23529411764705882, 'undercutter_attack': 0.21875, 'partial': 0.09090909090909091}, 'f1': {'support': 0.7363013698630138, 'agreement': 0.45569620253164556, 'direct_attack': 0.29090909090909084, 'undercutter_attack': 0.21538461538461537, 'partial': 0.15625}, 'support': {'support': 271, 'agreement': 32, 'direct_attack': 34, 'undercutter_attack': 64, 'partial': 55}, 'micro_avg': {'precision': 0.5701754385964912, 'recall': 0.5701754385964912, 'f1': 0.5701754385964912, 'support': None}, 'macro_avg': {'precision': 0.44370176609997153, 'recall': 0.3801622284270971, 'f1': 0.3709082557376731, 'support': None}, 'weighted_avg': {'precision': 0.5602832740724545, 'recall': 0.5701754385964912, 'f1': 0.5403272460294164, 'support': None}}
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2692e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6342e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6922e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2381e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9262e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0350e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9603e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6822e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9378e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5758e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3128e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9867e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9352e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1408e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6912e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9573e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7584e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0278e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0438e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9210e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9443e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4549e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1442e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7748e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3314e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2640e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2622e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5109e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7311e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9400e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9149e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7454e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9279e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8586e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1731e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5901e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6207e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6204e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5265e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8370e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7102e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4995e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1299e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5153e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0897e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4035e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2766e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2048e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5659e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1756e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7418e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3163e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0079e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5728e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3617e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5903e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3357e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8487e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3669e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1593e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8202e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8621e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7475e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9594e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0793e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3215e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0248e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9179e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4344e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9584e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3360e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7380e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6068e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4335e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2621e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7990e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5395e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1424e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3611e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3193e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9089e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5507e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2277e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9778e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4106e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5395e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9942e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3163e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4426e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2854e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4616e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3881e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6123e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5830e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9725e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8186e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5016e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1997e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1160e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9136e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2709e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8625e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6160e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7272e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1165e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6827e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5901e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7030e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5322e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6839e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1247e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5767e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1181e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9291e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2600e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1610e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6465e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7425e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0066e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3302e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6537e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5234e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0360e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9045e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6494e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3842e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6593e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8356e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5822e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3915e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3811e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5398e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5940e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8293e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6900e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2622e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0806e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5377e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0513e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7616e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9424e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4370e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5840e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2188e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7743e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0238e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7583e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6256e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3107e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4235e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7878e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2450e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5083e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8474e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4841e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1865e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4612e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6145e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5244e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3557e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6070e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2485e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0463e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3047e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2301e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6623e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6757e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4320e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2582e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3772e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2065e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9037e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5616e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6708e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5144e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6736e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1679e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7133e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8786e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3427e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9867e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3691e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0048e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2389e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9655e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3405e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8029e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8470e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1671e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2367e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1550e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1513e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7955e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1494e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2397e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1905e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4404e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7112e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7242e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4612e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5719e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4859e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3518e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2147e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2691e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7635e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5005e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7731e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6470e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8371e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7902e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2142e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2942e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9845e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6730e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1926e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5200e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2540e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2216e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1474e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1126e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9633e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7372e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1960e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0564e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3540e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4408e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7440e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4259e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3345e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9574e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2651e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7423e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3898e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8422e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0497e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3185e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8565e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4932e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9383e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3015e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0196e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2722e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0771e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3003e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4919e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9768e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9794e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4594e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5952e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1564e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9027e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4093e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5671e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9618e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7557e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4188e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7061e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4685e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1195e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9745e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7173e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5577e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2510e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2915e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6082e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7696e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6182e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3785e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7717e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3519e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3136e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9211e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8384e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4148e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8409e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7203e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5489e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5503e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0196e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5706e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3254e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0676e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7021e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2653e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7272e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5437e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3150e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8635e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8365e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3084e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4737e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1787e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8121e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7691e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2359e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9425e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3762e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4387e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4510e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4864e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2360e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9257e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6061e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5079e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1710e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0014e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2800e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9037e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5144e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0360e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5546e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2367e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5962e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5788e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4396e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3609e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1602e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0360e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0523e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6221e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0027e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5343e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3669e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5979e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5508e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3902e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7407e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6727e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3094e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7990e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2186e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8404e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0593e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8556e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0411e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2047e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1800e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8189e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8314e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0983e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9443e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5507e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6948e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5161e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2637e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1913e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3028e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1098e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5654e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2667e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3812e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9037e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3427e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7424e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3102e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5234e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8625e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6873e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5299e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0248e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6974e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7795e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4690e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5888e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9785e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1770e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5373e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5888e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1013e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7542e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3470e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3435e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1169e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5412e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0854e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0805e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1156e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6793e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0815e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9958e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8137e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9019e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3617e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0611e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7826e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3851e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7523e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5062e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6333e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6342e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5797e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1792e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2852e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5780e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0490e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3769e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0823e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8462e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4123e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6760e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5646e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6494e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2894e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8833e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1947e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7826e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7497e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3189e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2073e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1372e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0632e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 17---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6891025641025641, 'agreement': 0.4090909090909091, 'direct_attack': 0.34782608695652173, 'undercutter_attack': 0.208955223880597, 'partial': 0.5}, 'recall': {'support': 0.7933579335793358, 'agreement': 0.5625, 'direct_attack': 0.23529411764705882, 'undercutter_attack': 0.21875, 'partial': 0.09090909090909091}, 'f1': {'support': 0.7375643224699828, 'agreement': 0.47368421052631576, 'direct_attack': 0.28070175438596484, 'undercutter_attack': 0.21374045801526717, 'partial': 0.15384615384615385}, 'support': {'support': 271, 'agreement': 32, 'direct_attack': 34, 'undercutter_attack': 64, 'partial': 55}, 'micro_avg': {'precision': 0.5701754385964912, 'recall': 0.5701754385964912, 'f1': 0.5701754385964912, 'support': None}, 'macro_avg': {'precision': 0.4309949568061183, 'recall': 0.3801622284270971, 'f1': 0.37190737984873684, 'support': None}, 'weighted_avg': {'precision': 0.5538090465955787, 'recall': 0.5701754385964912, 'f1': 0.5410583630479074, 'support': None}}
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0865e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0680e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3227e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0611e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1673e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6324e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8561e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0256e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3503e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0138e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4063e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7644e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2291e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6598e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9058e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4208e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7011e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9374e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8958e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3802e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4253e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6048e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9200e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0360e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3115e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8080e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5706e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1407e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6433e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3245e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1505e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9240e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9797e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9067e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7216e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6882e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8142e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5485e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6146e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9673e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1260e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9876e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9957e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6515e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8879e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8423e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6627e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4798e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2440e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0998e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0529e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0922e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3738e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0390e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0956e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3526e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0460e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7113e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7787e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8894e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9031e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5533e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3512e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0581e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0209e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9071e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2856e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7220e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2838e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2467e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8643e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4638e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2164e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6243e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7831e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8251e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2259e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9279e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0166e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2458e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8232e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9495e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7666e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2047e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5023e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5101e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5174e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0101e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6879e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3652e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7536e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5237e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5750e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7743e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7815e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0161e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3821e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9028e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8520e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5606e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1351e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2424e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8059e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8756e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7363e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4015e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2769e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6748e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3946e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4823e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3526e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4306e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7484e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8734e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2410e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9023e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7729e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9536e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9106e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4568e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5827e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7756e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8171e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0351e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1481e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6532e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0763e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6727e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7493e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7644e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2792e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0110e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8712e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9621e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8020e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6494e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0282e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1874e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1602e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6954e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9088e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7202e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1316e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2251e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1826e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8859e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4577e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6345e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7696e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0896e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5464e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2942e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6152e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7989e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1360e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5325e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6218e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1329e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1471e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7021e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8918e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2164e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8954e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1596e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0130e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4922e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1998e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0914e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5026e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7229e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7457e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2177e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2769e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7064e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1731e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3245e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8652e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4995e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7242e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3842e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0330e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5004e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2340e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9512e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4206e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2921e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7644e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4105e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0672e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3535e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4677e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3067e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1740e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6805e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8643e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1198e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9590e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9191e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9370e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4292e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6796e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3431e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0027e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3147e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3996e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2117e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3738e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8907e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7947e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4889e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4992e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2706e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1986e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1186e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2566e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7622e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1013e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6337e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3617e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3560e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8574e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3617e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4677e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1292e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9552e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8704e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3420e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9391e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3699e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7614e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6241e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9857e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2933e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9059e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1165e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7622e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2891e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1130e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0096e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6282e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9076e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6667e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9037e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4910e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4858e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7523e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6558e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9845e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6697e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8868e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0321e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7746e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8894e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8621e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6216e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4942e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2813e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6065e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6848e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7985e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1868e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5831e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0347e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2967e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4585e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4793e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9725e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6416e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2637e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3166e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9542e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9227e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4972e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9614e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5563e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6254e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9573e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3055e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7886e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9465e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6712e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3647e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4538e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1955e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8828e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0745e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2246e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2073e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4737e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7656e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6835e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6706e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6684e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0997e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5691e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6606e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9069e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7296e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9287e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8068e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3578e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8916e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4865e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6849e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9834e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2914e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7977e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6173e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2590e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2497e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9323e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4547e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8140e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9270e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7142e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4927e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4049e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8937e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0096e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3327e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9893e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1800e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6091e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7224e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3119e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0149e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6411e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3989e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4060e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5788e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9728e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1541e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6363e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5101e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7977e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3205e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5616e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5667e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6433e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4589e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6403e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7434e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7476e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5373e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1200e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2782e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5256e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1242e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7943e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2419e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3716e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7484e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8786e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3193e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6932e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5891e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2373e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9802e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3306e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3146e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6719e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4100e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3792e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5708e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5049e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7989e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0848e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3245e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9499e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5005e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4184e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3763e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5494e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8627e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6218e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3325e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9092e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1762e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2951e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0127e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8665e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2146e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3700e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5525e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7296e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1990e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1770e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7920e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5823e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4715e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5434e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1610e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4223e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9461e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7051e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6022e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3292e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0796e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6160e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5204e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8678e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0663e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3238e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7293e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0412e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0049e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3166e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4939e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2570e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5091e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4710e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1589e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6143e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8401e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4577e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5585e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5533e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7021e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7182e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7688e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4344e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1377e-05, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 18---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6825396825396826, 'agreement': 0.3829787234042553, 'direct_attack': 0.4, 'undercutter_attack': 0.2153846153846154, 'partial': 0.5555555555555556}, 'recall': {'support': 0.7933579335793358, 'agreement': 0.5625, 'direct_attack': 0.23529411764705882, 'undercutter_attack': 0.21875, 'partial': 0.09090909090909091}, 'f1': {'support': 0.7337883959044369, 'agreement': 0.45569620253164556, 'direct_attack': 0.29629629629629634, 'undercutter_attack': 0.21705426356589147, 'partial': 0.15625}, 'support': {'support': 271, 'agreement': 32, 'direct_attack': 34, 'undercutter_attack': 64, 'partial': 55}, 'micro_avg': {'precision': 0.5701754385964912, 'recall': 0.5701754385964912, 'f1': 0.5701754385964912, 'support': None}, 'macro_avg': {'precision': 0.44729171537682183, 'recall': 0.3801622284270971, 'f1': 0.371817031659654, 'support': None}, 'weighted_avg': {'precision': 0.5595696141608796, 'recall': 0.5701754385964912, 'f1': 0.5394698041960662, 'support': None}}
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3072e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9863e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1316e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3042e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6805e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5187e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8253e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6340e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2358e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1952e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9287e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9530e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3792e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3802e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3298e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1558e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0765e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0193e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5347e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0360e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1063e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5555e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3185e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4720e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3130e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7471e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2043e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2107e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1289e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0564e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8068e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9543e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9252e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5676e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4922e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9927e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1974e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3853e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0672e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6191e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0690e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5295e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9463e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2337e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3133e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5408e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9361e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4382e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4802e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1783e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9762e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9725e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4413e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2341e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9651e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4897e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0862e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5833e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0275e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9945e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2574e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3275e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9836e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7895e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8604e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6566e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9798e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6233e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8613e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4859e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2345e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8870e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5789e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4750e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7150e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0762e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0633e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0884e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9230e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6212e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5888e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8323e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5594e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5345e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6942e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6631e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6160e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5384e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5222e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7467e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3064e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1264e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8249e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5827e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7115e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6282e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7678e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5879e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3751e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3950e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9436e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2721e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4867e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1965e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5156e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1338e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9741e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9898e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2733e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5385e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9049e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5546e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7804e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0075e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5356e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4529e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4798e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1247e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4374e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3799e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3656e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6881e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7250e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4650e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3254e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3482e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1485e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9089e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2943e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5789e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6303e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5485e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6887e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7088e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2224e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3591e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6805e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2701e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4776e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1671e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7925e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6334e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3046e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9141e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9692e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8695e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7757e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4195e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3254e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0632e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1891e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1601e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8302e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4106e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4049e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0451e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6646e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1973e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8137e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9826e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6576e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6303e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2358e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4292e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3811e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1736e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6887e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8280e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4547e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3003e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8413e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0996e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6160e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3063e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2535e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2899e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7707e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4980e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2709e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8756e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7332e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7562e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1329e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8954e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0217e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5477e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6643e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3829e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3288e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6082e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6191e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4489e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9020e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5715e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9386e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2055e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9837e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6295e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3807e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6108e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7938e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0870e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6381e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2367e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5016e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6136e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3782e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6796e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5424e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0256e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4231e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6298e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4398e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8936e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8341e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3267e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0835e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3124e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7588e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0559e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3368e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5248e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3496e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0745e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8871e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3594e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8496e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2125e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7438e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5285e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0193e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9469e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6902e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3700e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3784e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8833e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9564e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1074e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1035e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6433e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6819e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2554e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0351e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1312e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9736e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2987e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5142e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6956e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1029e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4080e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2450e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4789e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5032e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0551e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3459e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7911e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7568e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8305e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8940e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1053e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8750e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6277e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1861e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6878e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8120e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8712e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7242e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9339e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9000e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9461e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2532e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8500e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8213e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1277e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9954e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7720e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0088e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9069e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5386e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1663e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5740e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2034e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8323e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6659e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7241e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3075e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7516e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3662e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8062e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0983e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1368e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9279e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0007e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4162e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7596e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3866e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1398e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7644e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1701e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4387e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2234e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0776e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1338e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1431e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3388e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2217e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9733e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0736e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0724e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8828e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6710e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6506e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7111e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5407e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7849e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1005e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4004e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3682e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0196e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6463e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2026e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4011e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4227e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9120e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2610e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3665e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8638e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6648e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1437e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3988e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7817e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9636e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4126e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0735e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6706e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4597e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5070e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3007e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1792e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6297e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4071e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7911e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7285e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8492e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9058e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8401e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5930e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3721e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3825e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7194e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1095e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5079e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6130e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4690e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1551e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5392e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2579e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8474e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1826e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9361e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4147e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8583e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6778e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0226e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7747e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7768e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6677e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0650e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3033e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2912e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4500e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1018e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2298e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1913e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5896e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2198e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0775e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0693e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0517e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7475e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1147e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5931e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1925e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1371e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2618e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7003e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7302e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6506e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4599e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5566e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8916e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0885e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4413e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2164e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7605e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2298e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8597e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7435e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4789e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5698e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5330e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3149e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1035e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5210e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9015e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7384e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5639e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3085e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6091e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6760e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6290e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7422e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5343e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8344e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1883e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5177e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2510e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0369e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9769e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2076e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5456e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5633e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5092e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8515e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0420e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5533e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 19---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6816720257234726, 'agreement': 0.36363636363636365, 'direct_attack': 0.5, 'undercutter_attack': 0.21212121212121213, 'partial': 0.5}, 'recall': {'support': 0.7822878228782287, 'agreement': 0.625, 'direct_attack': 0.23529411764705882, 'undercutter_attack': 0.21875, 'partial': 0.07272727272727272}, 'f1': {'support': 0.7285223367697594, 'agreement': 0.4597701149425288, 'direct_attack': 0.31999999999999995, 'undercutter_attack': 0.21538461538461537, 'partial': 0.12698412698412698}, 'support': {'support': 271, 'agreement': 32, 'direct_attack': 34, 'undercutter_attack': 64, 'partial': 55}, 'micro_avg': {'precision': 0.5657894736842105, 'recall': 0.5657894736842105, 'f1': 0.5657894736842105, 'support': None}, 'macro_avg': {'precision': 0.45148592029620965, 'recall': 0.3868118426505121, 'f1': 0.37013223881620605, 'support': None}, 'weighted_avg': {'precision': 0.5579939477701366, 'recall': 0.5657894736842105, 'f1': 0.5346292528761143, 'support': None}}
Loss: tensor(7.4238e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9753e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4645e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4164e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3261e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6302e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0866e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7647e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7151e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2026e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1300e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8400e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2891e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8332e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6651e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3427e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3082e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8417e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3807e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8379e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7516e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7220e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0259e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7937e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1300e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8522e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0574e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5364e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5805e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7341e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9582e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8301e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1718e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4115e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6909e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6653e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0862e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9474e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9681e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1572e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5494e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7124e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3176e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6030e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3759e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5836e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8431e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3734e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2406e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4862e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8522e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5679e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1459e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0170e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4625e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9982e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2531e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5870e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7202e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5002e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7090e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6123e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2838e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4102e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7531e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1896e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2153e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0060e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1390e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3525e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3769e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9384e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6463e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3220e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8033e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2307e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0849e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6605e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8825e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4785e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1059e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5546e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5628e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6091e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0974e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7188e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4408e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5831e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2679e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6490e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7743e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2116e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8397e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0330e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5503e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7462e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2201e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5418e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0300e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0551e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2359e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8678e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5532e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0460e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6818e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3920e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4071e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4646e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3599e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0287e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3712e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3686e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8231e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1113e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2475e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1272e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9439e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4115e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2855e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9305e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7047e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4066e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6333e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7937e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3552e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0443e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5011e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9456e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4143e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8514e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1149e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4801e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1724e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7952e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7385e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3703e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1955e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3158e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1619e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0408e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4223e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8818e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4993e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2172e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9917e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2131e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8521e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8211e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4087e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1429e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3782e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2301e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1641e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5428e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4331e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5728e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8729e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8076e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1582e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8450e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4806e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0918e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1380e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6442e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9560e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9475e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2441e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1256e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3806e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5640e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3773e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7869e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8649e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7160e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4751e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0597e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7718e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2059e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3663e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8011e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0798e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3615e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3489e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6562e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7644e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1965e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0179e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3440e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5304e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3911e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0309e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9535e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6491e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5930e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2717e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4413e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9414e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4690e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3518e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5615e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8530e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8500e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7455e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2795e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9938e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3405e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8552e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6203e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9352e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6212e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9296e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1793e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4165e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8440e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6471e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2868e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4768e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5256e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2452e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1247e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7620e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7566e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7787e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1701e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5503e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8109e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6221e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4275e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0351e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0675e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5131e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4484e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7639e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8604e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9845e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9703e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3413e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8678e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6105e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6094e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9504e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0892e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5710e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5927e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6860e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2631e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0529e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6294e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5095e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1078e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8231e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1680e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1979e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4853e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8669e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4272e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7985e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1324e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9181e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6493e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7150e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1225e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7834e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6082e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8304e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8076e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6917e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4859e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0139e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9824e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1467e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3314e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1316e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1895e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6063e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0017e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5183e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2285e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8734e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5698e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3548e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6221e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7834e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3953e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4833e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5866e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0127e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7190e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8847e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8855e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5810e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9422e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5205e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2164e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6615e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4366e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5472e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5529e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5161e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7081e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7985e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7644e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6385e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4677e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0529e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0302e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6657e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6161e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6229e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9906e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5754e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3595e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1498e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8120e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9846e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8211e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3526e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9330e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4049e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8847e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7916e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5306e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1635e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1992e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1035e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0049e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2570e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8976e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2860e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8898e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9984e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2464e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8894e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2704e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3400e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3460e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9884e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2618e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9552e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9763e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0446e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8626e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2800e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9400e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7424e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7827e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9015e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4049e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7547e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0806e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9654e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6074e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7955e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4668e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0741e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3084e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2996e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9604e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7319e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8712e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5667e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9201e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3792e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9906e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7834e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9917e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7799e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5237e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1653e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2519e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6781e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7514e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1790e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6493e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7895e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6964e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5706e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1480e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9967e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5394e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7610e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2864e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6130e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4286e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9037e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1229e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9870e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0529e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3284e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5334e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8690e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8217e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8288e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3496e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8016e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8038e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2936e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4898e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1541e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3803e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0048e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3025e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2739e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4965e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4435e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7652e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7121e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0014e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8786e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9037e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8773e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4801e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3686e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9954e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4283e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7081e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3193e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9119e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2063e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0360e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6337e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3692e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4776e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0964e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0650e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7353e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2571e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4789e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1580e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3020e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0853e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5234e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8652e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6355e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7826e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3570e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2967e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5563e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3715e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9491e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1018e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5092e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8734e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4625e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5200e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3193e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7492e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9499e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6433e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3025e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5475e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8531e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2648e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9763e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7957e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7143e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8409e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8905e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4352e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4435e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2245e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4722e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8552e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1716e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0453e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8343e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4962e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3587e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6496e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8767e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4379e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1671e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0221e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8825e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1482e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2251e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6213e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6729e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9431e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4919e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4699e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5384e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7713e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2276e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7188e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4002e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3799e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4963e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3276e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1481e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5394e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0103e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8742e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6424e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6173e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5636e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5489e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3582e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0212e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7436e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0049e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9231e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7160e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2946e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2081e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1913e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9469e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7229e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1438e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9824e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5797e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0377e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7514e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6614e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9340e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9063e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2588e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 20---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6749226006191951, 'agreement': 0.4, 'direct_attack': 0.4444444444444444, 'undercutter_attack': 0.18055555555555555, 'partial': 0.625}, 'recall': {'support': 0.8044280442804428, 'agreement': 0.4375, 'direct_attack': 0.23529411764705882, 'undercutter_attack': 0.203125, 'partial': 0.09090909090909091}, 'f1': {'support': 0.734006734006734, 'agreement': 0.41791044776119407, 'direct_attack': 0.30769230769230765, 'undercutter_attack': 0.19117647058823528, 'partial': 0.15873015873015875}, 'support': {'support': 271, 'agreement': 32, 'direct_attack': 34, 'undercutter_attack': 64, 'partial': 55}, 'micro_avg': {'precision': 0.5657894736842105, 'recall': 0.5657894736842105, 'f1': 0.5657894736842105, 'support': None}, 'macro_avg': {'precision': 0.46498452012383906, 'recall': 0.3542512505673185, 'f1': 0.361903223755726, 'support': None}, 'weighted_avg': {'precision': 0.5630387970054135, 'recall': 0.5657894736842105, 'f1': 0.5344648038454547, 'support': None}}
Loss: tensor(3.2064e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8894e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8288e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0323e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3378e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5576e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2868e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5888e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6163e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9853e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7404e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2929e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7515e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2626e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2715e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5351e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6865e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8928e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7920e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3171e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1960e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0067e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1520e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4889e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2514e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7895e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0953e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1338e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0806e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7229e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8976e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7548e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2268e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3050e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5023e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3898e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0810e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6342e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9348e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4207e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6152e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3863e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2004e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8154e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8805e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7145e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5412e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0239e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6956e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4457e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8928e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8504e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5464e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6091e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5758e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1437e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4344e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7726e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3548e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3678e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3676e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7575e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6317e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9370e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9227e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6139e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4589e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0977e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0793e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8894e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9879e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8344e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6048e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2202e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5200e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9686e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1952e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0230e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2683e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9733e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3768e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4070e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8726e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0264e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0167e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3782e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4117e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0480e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0706e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4435e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2678e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3141e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0749e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2081e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8162e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(11.2591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1900, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0880, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5794, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6774, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0774, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1481, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5885, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1903, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0971, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2860, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4318e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6927, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0913, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2662, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0783, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7569, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1880, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0765, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2761, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0844, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4769, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9569, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9978, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0744, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0693, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4662, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3693, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3654, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2680, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0873, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3777, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6791, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2784, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2719, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0784, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0701, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7796, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1915, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3947, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8785, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3860, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2903, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0847, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6929, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1983, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3813, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4798, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9847, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0768e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7791, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3997, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3757, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4873e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3798, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0693, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0364e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0481, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7796, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0783, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0978, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8844, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0926, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4643e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1315, device='cuda:0', grad_fn=<DivBackward0>)


		-------------RUN 3-----------
			------------EPOCH 1---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.0, 'agreement': 0.0, 'direct_attack': 0.0, 'undercutter_attack': 0.0, 'partial': 0.07388316151202749}, 'recall': {'support': 0.0, 'agreement': 0.0, 'direct_attack': 0.0, 'undercutter_attack': 0.0, 'partial': 1.0}, 'f1': {'support': 0.0, 'agreement': 0.0, 'direct_attack': 0.0, 'undercutter_attack': 0.0, 'partial': 0.1376}, 'support': {'support': 374, 'agreement': 97, 'direct_attack': 34, 'undercutter_attack': 34, 'partial': 43}, 'micro_avg': {'precision': 0.07388316151202749, 'recall': 0.07388316151202749, 'f1': 0.07388316151202749, 'support': None}, 'macro_avg': {'precision': 0.014776632302405498, 'recall': 0.2, 'f1': 0.02752, 'support': None}, 'weighted_avg': {'precision': 0.0054587215550123405, 'recall': 0.07388316151202749, 'f1': 0.010166323024054983, 'support': None}}
Loss: tensor(0.9064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8994, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8720, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7962, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7761, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7671, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0906, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0912, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6773, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6635, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7654, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6962, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7791, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5994, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7840, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2660, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7604, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1705, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7693, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0956, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1662, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7797, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9683, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9847, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5977, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7652, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1753, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9903, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4837, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7955, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6950, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5900, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0740, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5784, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4874, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9601, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1817, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6616, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7750, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2922, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9873, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3730, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4985, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6972, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6940, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2868, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4929, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5913, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5912, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2985, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3904, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4784, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9671, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7868, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4831, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9784, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9783, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3957, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5801, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0744, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5604, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5862, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4798, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2913, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7921, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5922, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3987, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7744, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3806, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3998, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2978, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9852, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7738, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2374, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0965, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9831, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5940, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0900, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8806, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6813, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6826, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3806, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4927, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4635, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9754, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4773, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2632, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3751, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3753, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3885, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5652, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4604, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4947, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6921, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0935, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6761, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5906, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8761, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2797, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3378, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 2---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7934782608695652, 'agreement': 0.576271186440678, 'direct_attack': 0.07100591715976332, 'undercutter_attack': 0.02702702702702703, 'partial': 0.0}, 'recall': {'support': 0.5855614973262032, 'agreement': 0.35051546391752575, 'direct_attack': 0.35294117647058826, 'undercutter_attack': 0.058823529411764705, 'partial': 0.0}, 'f1': {'support': 0.6738461538461538, 'agreement': 0.4358974358974359, 'direct_attack': 0.11822660098522168, 'undercutter_attack': 0.03703703703703704, 'partial': 0.0}, 'support': {'support': 374, 'agreement': 97, 'direct_attack': 34, 'undercutter_attack': 34, 'partial': 43}, 'micro_avg': {'precision': 0.4587628865979381, 'recall': 0.4587628865979381, 'f1': 0.4587628865979381, 'support': None}, 'macro_avg': {'precision': 0.2935564782994067, 'recall': 0.2695683334252164, 'f1': 0.25300144555316967, 'support': None}, 'weighted_avg': {'precision': 0.6116706095400584, 'recall': 0.4587628865979381, 'f1': 0.514741368579501, 'support': None}}
Loss: tensor(2.6149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4831, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2929, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4601, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0662, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3654, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5898, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6783, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8801, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0868, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8906, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4553, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0900, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8922, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7481, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4740, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4553, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1935, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2720, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3730, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6873, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3784, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7852, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0837, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0720, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8511, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3806, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6817, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2761, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5965, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5956, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1935, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3927, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8769, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4837, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7971, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0701, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0847, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0880, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0601, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2754, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4719, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0935, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0947, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1671, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2757, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0898, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1714, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2785, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4601, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2719, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4744, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1837, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7947, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1765, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2774, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1654, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0769, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6694, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3983, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3862, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1874, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0753, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3843, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6783, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0987, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1904, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3569, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4978, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2791, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2604, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0904, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4929, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5831, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4714, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7616, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5693, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8900, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0374, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4885, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6950, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3757, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1601, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7374, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1374, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7985, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2791, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1641, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1740, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0874, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6713, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4791, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8660, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0994, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2560, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7913, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1660, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0840, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1900, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8817, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6635, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4898, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4560, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0705, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5652, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8826, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6783, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4797, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5962, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3868, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7739, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0921, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0680, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1662, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4732, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 3---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8203389830508474, 'agreement': 0.4074074074074074, 'direct_attack': 0.0, 'undercutter_attack': 0.09274193548387097, 'partial': 0.25}, 'recall': {'support': 0.6470588235294118, 'agreement': 0.1134020618556701, 'direct_attack': 0.0, 'undercutter_attack': 0.6764705882352942, 'partial': 0.06976744186046512}, 'f1': {'support': 0.7234678624813154, 'agreement': 0.1774193548387097, 'direct_attack': 0.0, 'undercutter_attack': 0.16312056737588654, 'partial': 0.10909090909090909}, 'support': {'support': 374, 'agreement': 97, 'direct_attack': 34, 'undercutter_attack': 34, 'partial': 43}, 'micro_avg': {'precision': 0.4793814432989691, 'recall': 0.4793814432989691, 'f1': 0.4793814432989691, 'support': None}, 'macro_avg': {'precision': 0.3140976651884252, 'recall': 0.30133978309616827, 'f1': 0.23461973875736414, 'support': None}, 'weighted_avg': {'precision': 0.6189493539278128, 'recall': 0.4793814432989691, 'f1': 0.5120681552732922, 'support': None}}
Loss: tensor(0.0685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1632, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0553, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3904, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1798, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0977, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8641, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2754, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1852, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1738, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2994, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3785, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0774, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6757, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2783, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1817, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5754, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5652, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0794, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0761, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6751, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6912, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1693, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1826, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0950, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3553, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1785, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0971, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9773, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1957, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2671, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4714, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1965, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0694, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2739, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6753, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0813, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0794, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5947, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0904, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3744, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5906, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1784, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2641, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3947, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4765, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1922, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0868, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0903, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0900, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0730, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3837, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6739, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6906, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3719, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2765, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3929, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0662, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3705, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0977, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0794, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2680, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0701, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1868, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1794, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0783, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0754, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4701, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0994, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3427, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0511, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0635, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2921, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0862, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0806, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0843, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1806, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0871, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5730, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0929, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0890, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1862, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4912, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0714, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0671, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3693, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7632, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0553, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0241, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 4---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8100263852242744, 'agreement': 0.43548387096774194, 'direct_attack': 0.22727272727272727, 'undercutter_attack': 0.12, 'partial': 0.09090909090909091}, 'recall': {'support': 0.820855614973262, 'agreement': 0.27835051546391754, 'direct_attack': 0.29411764705882354, 'undercutter_attack': 0.2647058823529412, 'partial': 0.046511627906976744}, 'f1': {'support': 0.8154050464807436, 'agreement': 0.339622641509434, 'direct_attack': 0.25641025641025644, 'undercutter_attack': 0.16513761467889906, 'partial': 0.06153846153846154}, 'support': {'support': 374, 'agreement': 97, 'direct_attack': 34, 'undercutter_attack': 34, 'partial': 43}, 'micro_avg': {'precision': 0.6099656357388317, 'recall': 0.6099656357388317, 'f1': 0.6099656357388317, 'support': None}, 'macro_avg': {'precision': 0.33673841487476686, 'recall': 0.3409082575511842, 'f1': 0.32762280412355893, 'support': None}, 'weighted_avg': {'precision': 0.6201171257630812, 'recall': 0.6099656357388317, 'f1': 0.6097657475487943, 'support': None}}
Loss: tensor(0.3713, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9660, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0971, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0680, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0797, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2783, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1868, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0817, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0774, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0840, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0998, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0962, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0977, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1998, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5831, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3757, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2871, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2601, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2671, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0761, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0773, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0978, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0757, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2926, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0652, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0481, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4950, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0871, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2714, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4873, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1826, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3940, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8427, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2983, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2801, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1852, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1972, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1801, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0813, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0511, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2635, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0913, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3956, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1796, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0701, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0641, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2750, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5860, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1994, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0511, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6978, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2784, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3922, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0956, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2738, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 5---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8167701863354038, 'agreement': 0.3157894736842105, 'direct_attack': 0.13513513513513514, 'undercutter_attack': 0.10909090909090909, 'partial': 0.15}, 'recall': {'support': 0.7032085561497327, 'agreement': 0.12371134020618557, 'direct_attack': 0.14705882352941177, 'undercutter_attack': 0.5294117647058824, 'partial': 0.06976744186046512}, 'f1': {'support': 0.7557471264367815, 'agreement': 0.17777777777777778, 'direct_attack': 0.14084507042253522, 'undercutter_attack': 0.1809045226130653, 'partial': 0.09523809523809525}, 'support': {'support': 374, 'agreement': 97, 'direct_attack': 34, 'undercutter_attack': 34, 'partial': 43}, 'micro_avg': {'precision': 0.5171821305841925, 'recall': 0.5171821305841925, 'f1': 0.5171821305841925, 'support': None}, 'macro_avg': {'precision': 0.3053571408491317, 'recall': 0.3146315852903355, 'f1': 0.270102518497651, 'support': None}, 'weighted_avg': {'precision': 0.6028476187981012, 'recall': 0.5171821305841925, 'f1': 0.5411144226636585, 'support': None}}
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0774, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6904, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0481, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4985, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0744, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0757, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0641, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0971, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1783, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5880, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8813, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1898, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0880, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0616, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1971, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0860, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 6---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7672811059907834, 'agreement': 0.38461538461538464, 'direct_attack': 0.14705882352941177, 'undercutter_attack': 0.25, 'partial': 0.125}, 'recall': {'support': 0.8903743315508021, 'agreement': 0.20618556701030927, 'direct_attack': 0.29411764705882354, 'undercutter_attack': 0.08823529411764706, 'partial': 0.046511627906976744}, 'f1': {'support': 0.8242574257425742, 'agreement': 0.2684563758389262, 'direct_attack': 0.19607843137254904, 'undercutter_attack': 0.13043478260869565, 'partial': 0.06779661016949153}, 'support': {'support': 374, 'agreement': 97, 'direct_attack': 34, 'undercutter_attack': 34, 'partial': 43}, 'micro_avg': {'precision': 0.6323024054982818, 'recall': 0.6323024054982818, 'f1': 0.6323024054982818, 'support': None}, 'macro_avg': {'precision': 0.3347910628271159, 'recall': 0.30508489352891177, 'f1': 0.2974047251464473, 'support': None}, 'weighted_avg': {'precision': 0.5895976390863321, 'recall': 0.6323024054982818, 'f1': 0.5985038645992252, 'support': None}}
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3796e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4854e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0635, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0769e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6826, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2767e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7439e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8125e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0654, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0947, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0767e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3228e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0913, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0868, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3624e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9799e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4896e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9596e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4278e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0623, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 7---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8262295081967214, 'agreement': 0.2608695652173913, 'direct_attack': 0.1896551724137931, 'undercutter_attack': 0.2962962962962963, 'partial': 0.11382113821138211}, 'recall': {'support': 0.6737967914438503, 'agreement': 0.18556701030927836, 'direct_attack': 0.3235294117647059, 'undercutter_attack': 0.23529411764705882, 'partial': 0.32558139534883723}, 'f1': {'support': 0.7422680412371134, 'agreement': 0.21686746987951808, 'direct_attack': 0.2391304347826087, 'undercutter_attack': 0.2622950819672131, 'partial': 0.1686746987951807}, 'support': {'support': 374, 'agreement': 97, 'direct_attack': 34, 'undercutter_attack': 34, 'partial': 43}, 'micro_avg': {'precision': 0.520618556701031, 'recall': 0.520618556701031, 'f1': 0.520618556701031, 'support': None}, 'macro_avg': {'precision': 0.3373743360671168, 'recall': 0.34875374530274617, 'f1': 0.3258471453323268, 'support': None}, 'weighted_avg': {'precision': 0.6112213793314315, 'recall': 0.520618556701031, 'f1': 0.5548898137778014, 'support': None}}
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2730, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3573e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0652, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8799e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9900e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6548e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0874, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0683, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2846e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8184e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6973e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0293e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7657e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6196e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3221e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4553, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7557e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9860e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4348e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2674e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7124e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6579e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8808e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6688e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5743e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6246e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7454e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2138e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4621e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5299e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1049e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7769e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1504e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2846e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4542e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5592e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3673e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1502e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3258e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 8---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8362068965517241, 'agreement': 0.34328358208955223, 'direct_attack': 0.1650485436893204, 'undercutter_attack': 0.11864406779661017, 'partial': 0.4}, 'recall': {'support': 0.7780748663101604, 'agreement': 0.23711340206185566, 'direct_attack': 0.5, 'undercutter_attack': 0.20588235294117646, 'partial': 0.046511627906976744}, 'f1': {'support': 0.8060941828254847, 'agreement': 0.2804878048780488, 'direct_attack': 0.24817518248175183, 'undercutter_attack': 0.15053763440860216, 'partial': 0.08333333333333333}, 'support': {'support': 374, 'agreement': 97, 'direct_attack': 34, 'undercutter_attack': 34, 'partial': 43}, 'micro_avg': {'precision': 0.584192439862543, 'recall': 0.584192439862543, 'f1': 0.584192439862543, 'support': None}, 'macro_avg': {'precision': 0.37263661802544135, 'recall': 0.35351644984403385, 'f1': 0.31372562758544414, 'support': None}, 'weighted_avg': {'precision': 0.6406966246796444, 'recall': 0.584192439862543, 'f1': 0.5942029391022463, 'support': None}}
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4630e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1069e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8437e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9452e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6196e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3894e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5359e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0051e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7862e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5742e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8264e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3593e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1787e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9879e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2149e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1162e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9010e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4913e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6579e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4759e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0663e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2573e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2676e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8579e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3391e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3753e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8589e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1626e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4530e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7448e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1171e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7317e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6773e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1381e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2411e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7779e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8163e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7363e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4289e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9301e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0930e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3077e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0261e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1039e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0676e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3311e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8243e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4260e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9919e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2392e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4591e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1959e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6182e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4569e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4723e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0412e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9426e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7548e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6347e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5934e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9003e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6851e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 9---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8082901554404145, 'agreement': 0.36666666666666664, 'direct_attack': 0.2222222222222222, 'undercutter_attack': 0.11538461538461539, 'partial': 0.13636363636363635}, 'recall': {'support': 0.8342245989304813, 'agreement': 0.2268041237113402, 'direct_attack': 0.23529411764705882, 'undercutter_attack': 0.2647058823529412, 'partial': 0.06976744186046512}, 'f1': {'support': 0.8210526315789474, 'agreement': 0.2802547770700637, 'direct_attack': 0.22857142857142856, 'undercutter_attack': 0.16071428571428573, 'partial': 0.09230769230769229}, 'support': {'support': 374, 'agreement': 97, 'direct_attack': 34, 'undercutter_attack': 34, 'partial': 43}, 'micro_avg': {'precision': 0.6082474226804123, 'recall': 0.6082474226804123, 'f1': 0.6082474226804123, 'support': None}, 'macro_avg': {'precision': 0.329785459215511, 'recall': 0.32615923290045734, 'f1': 0.3165801630484836, 'support': None}, 'weighted_avg': {'precision': 0.6103255217244854, 'recall': 0.6082474226804123, 'f1': 0.603888904881903, 'support': None}}
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1524e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9928e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7438e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7212e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4156e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8414e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8113e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2282e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9969e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5107e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1889e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8526e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7568e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5470e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7233e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9686e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5592e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3751e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5931e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4653e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1525e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2795e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9404e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7066e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5923e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2171e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8455e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6779e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8476e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3886e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8689e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7861e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0769e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5913e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5885e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6791e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9162e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5520e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2049e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4187e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0412e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6004e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3978e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1927e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3805e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2918e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6649e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9446e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2664e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3713e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2038e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7376e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3512e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0111e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5520e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6770e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5398e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7014e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9392e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0836e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9546e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4499e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1242e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4260e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8356e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4026e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2398e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1502e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9245e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8365e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3432e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8063e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5680e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4188e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5447e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7660e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7469e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3352e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0616e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3279e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1726e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8084e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1441e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6529e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1877e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1444e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0264e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2280e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0818e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6394e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 10---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7944162436548223, 'agreement': 0.2972972972972973, 'direct_attack': 0.19117647058823528, 'undercutter_attack': 0.13043478260869565, 'partial': 0.21428571428571427}, 'recall': {'support': 0.8368983957219251, 'agreement': 0.1134020618556701, 'direct_attack': 0.38235294117647056, 'undercutter_attack': 0.2647058823529412, 'partial': 0.06976744186046512}, 'f1': {'support': 0.8151041666666667, 'agreement': 0.16417910447761194, 'direct_attack': 0.2549019607843137, 'undercutter_attack': 0.17475728155339806, 'partial': 0.10526315789473685}, 'support': {'support': 374, 'agreement': 97, 'direct_attack': 34, 'undercutter_attack': 34, 'partial': 43}, 'micro_avg': {'precision': 0.5996563573883161, 'recall': 0.5996563573883161, 'f1': 0.5996563573883161, 'support': None}, 'macro_avg': {'precision': 0.32552210168695295, 'recall': 0.3334253445934944, 'f1': 0.3028411342753455, 'support': None}, 'weighted_avg': {'precision': 0.5946711018689395, 'recall': 0.5996563573883161, 'f1': 0.5840361881385183, 'support': None}}
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8578e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6385e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6578e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6801e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3158e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6379e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5388e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9231e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7910e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9728e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9904, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5682e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8254e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9830e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5275e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5783e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6074e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8838e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3972e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9997e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2009e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4438e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3330e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9867e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3855e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8877e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8183e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0020e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0228e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4602e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9515e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7757e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2746e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7993e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2482e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9979e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1101e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2179e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8861e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8699e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8193e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7536e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2692e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2917e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7579e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2026e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8423e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1070e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4126e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5490e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7184e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0745e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7376e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3146e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7942e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0403e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7859e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6790e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8141e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3258e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6800e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4581e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0161e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4239e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3582e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3140e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2876e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9728e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7475e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6588e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0990e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5499e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3047e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9396e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0626e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1662e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8680e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2864e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5743e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8738e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9001e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1626e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4289e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5910e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3067e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6186e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8386e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3736e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4772e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2854e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2713e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6245e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0657e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3775e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3097e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2259e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3109e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6218e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0011e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1290e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0341e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0181e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0918e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8063e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8022e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8829e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9041e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7629e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6742e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8072e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1946e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4145e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6618e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5217e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1471e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2704e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2238e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4865e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2519e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1281e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0030e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9080e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1442e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3987e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5952e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 11---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7917737789203085, 'agreement': 0.25, 'direct_attack': 0.22641509433962265, 'undercutter_attack': 0.13580246913580246, 'partial': 0.2}, 'recall': {'support': 0.8235294117647058, 'agreement': 0.1134020618556701, 'direct_attack': 0.35294117647058826, 'undercutter_attack': 0.3235294117647059, 'partial': 0.06976744186046512}, 'f1': {'support': 0.8073394495412843, 'agreement': 0.15602836879432624, 'direct_attack': 0.27586206896551724, 'undercutter_attack': 0.19130434782608696, 'partial': 0.10344827586206895}, 'support': {'support': 374, 'agreement': 97, 'direct_attack': 34, 'undercutter_attack': 34, 'partial': 43}, 'micro_avg': {'precision': 0.5927835051546392, 'recall': 0.5927835051546392, 'f1': 0.5927835051546392, 'support': None}, 'macro_avg': {'precision': 0.3207982684791467, 'recall': 0.336633900743227, 'f1': 0.30679650219785676, 'support': None}, 'weighted_avg': {'precision': 0.5864068564851544, 'recall': 0.5927835051546392, 'f1': 0.5797450857980644, 'support': None}}
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4662e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2332e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6742e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7536e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1190e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7205e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3490e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0230e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9101e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6900e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9213e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9083e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6364e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7185e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1311e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8150e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8285e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2471e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6497e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4087e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6640e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6490e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4962e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3540e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9454e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0451e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1533e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0384e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5531e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9739e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3894e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6113e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2037e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1889e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0261e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7922e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5014e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3127e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8647e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2633e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3288e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9110e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3621e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8700e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4561e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4084e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1504e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4207e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1947e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9686e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9273e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6379e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3903e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9011e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7376e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7600e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0504e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3179e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2177e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0072e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7908e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4439e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8677e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6782e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2582e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8617e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1070e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7850e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6315e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4630e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4720e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2280e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0391e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8816e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5279e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9528e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0748e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2110e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0151e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9827e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5420e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3158e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6446e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5252e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6457e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8909e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0451e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3098e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2834e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8587e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3188e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6973e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6658e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6228e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4985e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5138e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5032e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3098e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6499e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3652e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8475e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8405e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8726e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0778e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2331e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2856e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3139e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6731e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8286e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5007e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8889e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6610e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3936e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0294e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6749e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7738e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2830e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8667e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3209e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4154e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8770e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4218e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3019e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3845e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6397e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7497e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7190e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5752e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6255e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6177e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2057e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4562e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9053e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3669e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6667e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 12---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8091397849462365, 'agreement': 0.3137254901960784, 'direct_attack': 0.19672131147540983, 'undercutter_attack': 0.14285714285714285, 'partial': 0.14285714285714285}, 'recall': {'support': 0.8048128342245989, 'agreement': 0.16494845360824742, 'direct_attack': 0.35294117647058826, 'undercutter_attack': 0.3235294117647059, 'partial': 0.06976744186046512}, 'f1': {'support': 0.806970509383378, 'agreement': 0.21621621621621623, 'direct_attack': 0.2526315789473684, 'undercutter_attack': 0.1981981981981982, 'partial': 0.09374999999999999}, 'support': {'support': 374, 'agreement': 97, 'direct_attack': 34, 'undercutter_attack': 34, 'partial': 43}, 'micro_avg': {'precision': 0.5893470790378007, 'recall': 0.5893470790378007, 'f1': 0.5893470790378007, 'support': None}, 'macro_avg': {'precision': 0.32106017446640206, 'recall': 0.3431998635857211, 'f1': 0.31355330054903213, 'support': None}, 'weighted_avg': {'precision': 0.6026429153076908, 'recall': 0.5893470790378007, 'f1': 0.5878683950262983, 'support': None}}
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8271e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8292e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2089e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5429e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5910e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8060e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7363e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4326e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0503e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5461e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3803e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2037e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9071e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6074e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4563e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7638e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9295e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7126e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6287e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4487e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1704e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0182e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3945e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1635e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5420e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4823e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7256e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8244e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0846e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0616e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6276e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0848e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5910e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0413e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3501e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9664e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7657e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4580e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5893e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9325e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5498e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6954e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6970e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3854e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6752e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6902e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1995e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4551e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2207e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9548e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3104e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3320e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7757e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7509e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4569e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8213e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8838e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6379e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5631e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9758e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7506e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5065e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0048e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0091e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7992e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5728e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7710e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6013e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3751e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3076e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0827e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5304e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0898e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5783e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7064e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5177e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4008e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4278e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8345e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1280e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8477e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4076e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3119e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8317e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6567e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4166e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5993e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0572e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2141e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7596e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3774e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4418e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8341e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3158e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6303e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9334e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9738e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0808e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6258e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7445e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5659e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9334e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1463e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8529e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3127e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4175e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0384e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4441e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8576e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3896e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2585e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1120e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3278e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6709e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6394e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4583e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0332e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6558e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1745e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0585e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4703e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6870e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6074e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3551e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6156e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1048e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9656e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0364e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9676e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0706e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0656e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9292e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8032e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7163e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9122e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0485e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3371e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0442e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9625e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9040e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6675e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1321e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2645e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6066e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8032e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3401e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9101e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9988e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7739e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7920e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2400e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5822e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3639e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5945e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8498e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0606e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8940e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2428e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0360e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1238e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2885e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3339e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0823e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5970e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8362e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0767e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3307e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5094e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9384e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 13---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8181818181818182, 'agreement': 0.36764705882352944, 'direct_attack': 0.20512820512820512, 'undercutter_attack': 0.14634146341463414, 'partial': 0.15789473684210525}, 'recall': {'support': 0.8181818181818182, 'agreement': 0.25773195876288657, 'direct_attack': 0.23529411764705882, 'undercutter_attack': 0.35294117647058826, 'partial': 0.06976744186046512}, 'f1': {'support': 0.8181818181818182, 'agreement': 0.30303030303030304, 'direct_attack': 0.2191780821917808, 'undercutter_attack': 0.20689655172413793, 'partial': 0.09677419354838708}, 'support': {'support': 374, 'agreement': 97, 'direct_attack': 34, 'undercutter_attack': 34, 'partial': 43}, 'micro_avg': {'precision': 0.6082474226804123, 'recall': 0.6082474226804123, 'f1': 0.6082474226804123, 'support': None}, 'macro_avg': {'precision': 0.3390386564780584, 'recall': 0.3467833025845634, 'f1': 0.3288121897352854, 'support': None}, 'weighted_avg': {'precision': 0.6192460603445866, 'recall': 0.6082474226804123, 'f1': 0.608319187748559, 'support': None}}
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7402e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6316e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6667e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9071e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2904e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0242e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5611e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2431e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1341e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3309e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6791e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4699e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5023e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7405e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6547e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8695e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1571e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3291e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2622e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1753e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3100e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6213e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8598e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4426e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8398e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4449e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3067e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0269e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8425e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8761e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9289e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7569e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4875e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1026e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2824e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1126e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0536e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4664e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4154e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2752e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5873e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9008e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7971e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2158e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0707e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2492e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7003e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8786e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9394e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2684e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6146e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9270e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5667e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0283e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1169e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3873e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9028e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0736e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4993e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7493e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9751, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6618e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6122e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2977e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7990e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1374e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0273e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8184e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3449e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8042e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9031e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0312e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5014e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0611e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8353e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1593e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1068e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8444e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4721e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9261e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4663e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6823e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1799e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1886e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5598e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7960e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6887e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9355e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4651e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5326e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2311e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2389e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5237e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5904e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9343e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6367e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6245e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4578e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2733e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8595e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9846e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5155e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0633e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3954e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0524e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4041e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2337e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4729e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1481e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0141e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5761e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9467e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6236e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7000e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3200e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9279e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5741e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6688e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7263e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2713e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3500e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6255e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1524e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1865e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8132e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4296e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0263e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8604e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8559e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2108e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1550e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6879e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4713e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0100e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8807e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3209e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9262e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0081e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9443e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1947e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3067e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8868e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6667e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3025e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2988e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7242e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7799e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3794e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2579e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9071e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3398e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7881e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4094e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0666e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7717e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4478e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7749e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8314e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4825e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1574e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0403e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7969e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9019e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6887e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5174e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5851e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0969e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9988e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6939e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2471e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1859e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7861e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9867e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4411e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0604e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0118e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3942e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3630e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8780e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7206e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7499e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5377e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7004e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1437e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5940e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6809e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8877e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2131e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3064e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8122e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8565e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7324e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1411e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8726e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9092e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3742e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4066e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4620e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4387e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8232e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1856e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4560e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2544e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1078e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4861e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4448e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2246e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0936e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2277e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4175e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7114e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 14---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8021108179419525, 'agreement': 0.22857142857142856, 'direct_attack': 0.18181818181818182, 'undercutter_attack': 0.12658227848101267, 'partial': 0.17391304347826086}, 'recall': {'support': 0.8128342245989305, 'agreement': 0.08247422680412371, 'direct_attack': 0.35294117647058826, 'undercutter_attack': 0.29411764705882354, 'partial': 0.09302325581395349}, 'f1': {'support': 0.8074369189907039, 'agreement': 0.1212121212121212, 'direct_attack': 0.24000000000000002, 'undercutter_attack': 0.1769911504424779, 'partial': 0.12121212121212122}, 'support': {'support': 374, 'agreement': 97, 'direct_attack': 34, 'undercutter_attack': 34, 'partial': 43}, 'micro_avg': {'precision': 0.5807560137457045, 'recall': 0.5807560137457045, 'f1': 0.5807560137457045, 'support': None}, 'macro_avg': {'precision': 0.30259915005816734, 'recall': 0.3270781061492839, 'f1': 0.29337046237148484, 'support': None}, 'weighted_avg': {'precision': 0.5844067886622966, 'recall': 0.5807560137457045, 'f1': 0.5723862608028599, 'support': None}}
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3766e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8332e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8800e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4115e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4456e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0382e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6730e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3085e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5195e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0672e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2583e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7354e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6962e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1735e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1580e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1281e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2038e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6195e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1896e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3852e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1310e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9657e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5974e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9164e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8298e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3573e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8556e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0049e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2704e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4683e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1429e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7375e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8444e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0442e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1550e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8081e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7506e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7333e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1343e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8051e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1489e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6993e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1619e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8194e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4356e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2298e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4309e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7165e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4824e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5377e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0127e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0602e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9061e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3015e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6036e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7151e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7493e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7462e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7557e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8050e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2955e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9123e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5101e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3754e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9673e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8689e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1005e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7674e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8679e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9262e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8734e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6070e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9494e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1423e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6730e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5185e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0947e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1664e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9067e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6035e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4409e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7011e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6255e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7827e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8959e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2289e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8068e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3926e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5874e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2522e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9673e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1312e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8172e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2722e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8020e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3258e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3055e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5040e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9361e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5297e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4244e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4123e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8513e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7910e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3176e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6661e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6852e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1421e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4075e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7700e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8889e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9604e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5853e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8604e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3452e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8796e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9625e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9252e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0408e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0352e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1256e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5892e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9162e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7569e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0374e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0634e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4175e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9254e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6476e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5304e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0724e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8211e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3236e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5076e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6666e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9612e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8709e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2120e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9540e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4370e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9699e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5464e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5559e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4439e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7790e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4024e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5287e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7397e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2765e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0334e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8846e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7859e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5608e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1481e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6094e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4371e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3630e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9625e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5819e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4750e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9031e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3409e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5560e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0292e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6559e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7415e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3137e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2401e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5922e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9979e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4223e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7194e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3318e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8135e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7908e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8004e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7569e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5540e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1271e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1368e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2369e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3100e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6386e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6718e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5378e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3512e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3531e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8629e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9333e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1777e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1913e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0101e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8050e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2555e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0827e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1513e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4790e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5258e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7809e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9646e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6221e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9928e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8898e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4448e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4902e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1473e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3137e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7799e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4139e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4932e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5434e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9252e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5034e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9455e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1111e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5546e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4465e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7247e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6074e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0545e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9513e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2246e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9465e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3976e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2882e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7163e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1605e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3652e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2332e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3276e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3926e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2540e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9785e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1898e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6065e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0766e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9634e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6548e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7341e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6903e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 15---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8031914893617021, 'agreement': 0.2571428571428571, 'direct_attack': 0.18072289156626506, 'undercutter_attack': 0.136986301369863, 'partial': 0.2}, 'recall': {'support': 0.8074866310160428, 'agreement': 0.09278350515463918, 'direct_attack': 0.4411764705882353, 'undercutter_attack': 0.29411764705882354, 'partial': 0.06976744186046512}, 'f1': {'support': 0.8053333333333333, 'agreement': 0.13636363636363635, 'direct_attack': 0.2564102564102564, 'undercutter_attack': 0.18691588785046728, 'partial': 0.10344827586206895}, 'support': {'support': 374, 'agreement': 97, 'direct_attack': 34, 'undercutter_attack': 34, 'partial': 43}, 'micro_avg': {'precision': 0.5824742268041238, 'recall': 0.5824742268041238, 'f1': 0.5824742268041238, 'support': None}, 'macro_avg': {'precision': 0.3156087078881375, 'recall': 0.34106633913564116, 'f1': 0.2976942779639525, 'support': None}, 'weighted_avg': {'precision': 0.5923343414501067, 'recall': 0.5824742268041238, 'f1': 0.5737857459808814, 'support': None}}
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8969e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3218e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7069e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7194e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3427e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8310e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1623e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4572e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2310e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7251e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2934e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2471e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4916e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8737e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1187e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3873e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6406e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6113e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2750e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8940e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2098e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2358e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0312e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2743e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5810e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7598e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5801e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6016e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2371e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1432e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6004e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8616e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6701e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6285e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5326e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8677e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6858e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5783e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2099e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9909e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3660e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8638e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4396e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8447e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5550e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3600e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4278e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1874e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0927e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8333e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7272e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2340e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5126e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8164e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2807e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0343e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0261e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7354e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6796e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3745e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6152e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6636e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3260e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7681e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5234e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6945e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0131e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7862e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5266e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8132e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1593e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8425e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4078e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4378e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4430e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6385e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5637e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3039e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2709e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3972e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4529e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3872e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4660e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5153e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8526e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7151e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3146e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0897e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2383e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2471e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7163e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0430e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9738e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2380e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6485e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4187e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2432e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5026e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7577e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8818e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1995e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3473e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8740e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1402e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4993e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1096e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2017e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9302e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9163e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5265e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3358e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8492e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0745e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1026e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2038e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7233e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9153e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4390e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2467e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2887e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9171e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2613e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1535e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8464e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9365e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4853e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6061e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6759e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6770e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6074e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5956e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3876e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3708e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9343e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2882e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0415e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8323e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1511e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6285e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6074e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8141e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1927e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9945e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9385e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9961e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5247e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8323e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7584e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1783e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1139e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8365e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5144e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0351e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4965e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2389e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3228e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6757e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1493e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8245e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0027e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3448e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5407e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5213e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8877e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2667e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2276e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0140e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7798e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7726e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3754e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8829e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8343e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9573e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4550e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4559e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1429e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4396e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5386e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4348e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0754e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6507e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4054e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7082e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7303e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9080e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8916e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4175e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7471e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8059e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8068e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5511e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6355e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1956e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1057e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7779e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9556e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4154e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5942e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8129e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0442e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8595e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2043e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6973e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1320e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1480e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9158e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3215e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9836e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5649e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7462e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3127e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5358e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7639e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2300e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9543e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4741e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4841e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0203e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7657e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8889e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0222e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1156e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1783e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1968e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0420e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9957e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6921e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6055e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9888e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5788e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4348e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9461e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0314e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3942e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9062e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2099e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3076e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6379e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7173e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6640e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9746e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2824e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2996e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9361e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9828e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8535e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2043e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4647e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1381e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7969e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1633e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4468e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3094e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4002e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0278e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3397e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3427e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7999e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2056e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6064e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1299e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2500e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3328e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3163e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7366e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4616e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9515e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7266e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3258e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9499e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5993e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6175e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6851e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9028e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0641e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5560e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6082e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3609e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4789e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3609e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6435e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5438e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5206e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2585e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2026e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6295e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4729e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3033e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0290e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3825e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0270e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9826e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6590e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1177e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1511e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2541e-05, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 16---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7952755905511811, 'agreement': 0.25, 'direct_attack': 0.18840579710144928, 'undercutter_attack': 0.14102564102564102, 'partial': 0.16666666666666666}, 'recall': {'support': 0.8101604278074866, 'agreement': 0.09278350515463918, 'direct_attack': 0.38235294117647056, 'undercutter_attack': 0.3235294117647059, 'partial': 0.06976744186046512}, 'f1': {'support': 0.8026490066225166, 'agreement': 0.13533834586466165, 'direct_attack': 0.25242718446601947, 'undercutter_attack': 0.19642857142857145, 'partial': 0.09836065573770493}, 'support': {'support': 374, 'agreement': 97, 'direct_attack': 34, 'undercutter_attack': 34, 'partial': 43}, 'micro_avg': {'precision': 0.5824742268041238, 'recall': 0.5824742268041238, 'f1': 0.5824742268041238, 'support': None}, 'macro_avg': {'precision': 0.3082747390689876, 'recall': 0.33571874555275344, 'f1': 0.29704075282389486, 'support': None}, 'weighted_avg': {'precision': 0.5842790488473014, 'recall': 0.5824742268041238, 'f1': 0.571837030795242, 'support': None}}
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8385e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4102e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7372e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7667e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2665e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4821e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0554e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9776e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1407e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5659e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3250e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1922e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4005e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9798e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7338e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5849e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0181e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8481e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0312e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6636e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0838e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6688e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1360e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7971e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0321e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5213e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4733e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9292e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3439e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8998e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9845e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5208e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5667e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9400e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5186e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8083e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7473e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3993e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9188e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7506e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9119e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5316e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1229e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6214e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1450e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5982e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9612e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4771e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2967e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6547e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4387e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9059e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0187e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9921e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4707e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8535e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4216e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5404e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3916e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4923e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2665e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9698e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8098e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2186e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7938e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8431e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0049e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9534e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3237e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1005e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7588e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8535e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2562e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7212e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8505e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6912e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6903e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0060e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2761e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7847e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3963e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3661e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5870e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7133e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3394e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0503e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3154e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8950e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3682e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2191e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3893e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5970e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5459e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1026e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8780e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1558e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0572e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6385e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2915e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4236e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8786e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4093e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4093e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8125e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3094e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6013e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2588e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2653e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7925e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4408e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3058e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4660e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6952e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0859e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9815e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6999e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7696e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0696e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2410e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2618e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0377e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6372e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8786e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0312e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2921e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7789e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2743e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8940e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0836e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2864e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5327e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6195e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2371e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7726e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4084e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9269e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5641e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6524e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1340e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5901e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7476e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8159e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1972e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9666e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9422e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1967e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2761e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0978e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3977e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7151e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1814e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8505e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9218e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8952e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6031e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7709e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2964e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4569e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5558e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2648e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6122e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7069e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6561e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5328e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0166e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3561e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6276e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6963e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4117e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7276e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5123e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0551e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3963e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7635e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5862e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1843e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3803e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9627e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5894e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8464e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9979e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2069e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4451e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2834e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3221e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6152e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7232e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8727e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3361e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7062e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0027e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0446e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6358e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6638e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5408e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5131e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7810e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6260e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2389e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8816e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5827e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6091e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2713e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8395e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1005e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0353e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9474e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6779e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8628e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8239e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6758e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5598e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7181e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9776e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1277e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0953e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2579e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4114e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5156e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8068e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4974e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2825e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7363e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2108e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1117e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9725e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6818e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0060e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5365e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9153e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7398e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6315e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8626e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2783e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8637e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2367e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5862e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5477e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9906e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7938e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5001e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6122e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4335e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8658e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9564e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0442e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6383e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4318e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6022e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6748e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1641e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8940e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7051e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8738e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6324e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7143e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4439e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3654e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6498e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4884e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8576e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3176e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0148e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6709e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4435e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8293e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8695e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4457e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5410e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2156e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9424e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4887e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5762e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5894e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5871e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8383e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8184e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9817e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3548e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8968e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0369e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0845e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3531e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2753e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2640e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1513e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1822e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2255e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8838e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3734e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8344e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9113e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2380e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9987e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7376e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6969e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8314e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9099e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7485e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2285e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3472e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1740e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5467e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3470e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7614e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9221e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 17---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8, 'agreement': 0.21428571428571427, 'direct_attack': 0.19672131147540983, 'undercutter_attack': 0.14666666666666667, 'partial': 0.15789473684210525}, 'recall': {'support': 0.8235294117647058, 'agreement': 0.09278350515463918, 'direct_attack': 0.35294117647058826, 'undercutter_attack': 0.3235294117647059, 'partial': 0.06976744186046512}, 'f1': {'support': 0.8115942028985507, 'agreement': 0.1294964028776978, 'direct_attack': 0.2526315789473684, 'undercutter_attack': 0.2018348623853211, 'partial': 0.09677419354838708}, 'support': {'support': 374, 'agreement': 97, 'direct_attack': 34, 'undercutter_attack': 34, 'partial': 43}, 'micro_avg': {'precision': 0.5893470790378007, 'recall': 0.5893470790378007, 'f1': 0.5893470790378007, 'support': None}, 'macro_avg': {'precision': 0.30311368585397924, 'recall': 0.3325101894030208, 'f1': 0.29846624813146494, 'support': None}, 'weighted_avg': {'precision': 0.5815298612143563, 'recall': 0.5893470790378007, 'f1': 0.5768222204314205, 'support': None}}
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7998e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9021e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3622e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1703e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8275e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6736e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2915e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0260e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5429e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7913e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3672e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8323e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4761e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8081e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9443e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9819e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8125e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3085e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7977e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1035e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8284e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3198e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5095e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3526e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7459e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1864e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8254e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5701e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2692e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4668e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8444e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5706e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9590e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4932e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3405e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3310e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3350e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9482e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1398e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8462e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6688e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0905e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0182e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8607e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2307e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4971e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7583e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0049e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5325e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8411e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5948e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4586e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4628e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1378e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9754e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0663e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1571e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5196e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8197e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0784e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2601e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5360e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4417e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8900e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5189e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8771e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1351e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3461e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8487e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8878e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3903e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2379e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8665e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2670e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9646e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3266e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2328e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9274e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4184e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1956e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0868e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0464e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1512e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3880e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4179e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6372e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5570e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2282e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6839e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8271e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8464e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3480e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8486e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6930e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2899e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1008e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2397e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6808e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3821e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1632e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9223e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4902e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6818e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7842e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1211e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7105e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4540e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1199e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1489e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8375e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9439e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8825e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1947e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7619e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4710e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4392e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7685e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0736e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1498e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1780e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7375e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9673e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6961e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4935e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2177e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1710e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2137e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8825e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5177e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1210e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6275e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8184e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4643e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6719e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9244e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9007e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2098e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0442e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2379e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0680e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8090e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9003e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8860e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3487e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9122e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2813e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7920e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6622e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7999e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0246e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7677e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0211e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1495e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8919e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9061e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4560e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1028e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0875e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1511e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9020e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6872e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6931e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8686e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4457e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2238e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3237e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9543e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6000e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6658e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8250e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1891e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1462e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1831e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5195e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0226e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8390e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9544e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2695e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1982e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8318e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9677e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6891e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1754e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5700e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7957e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8232e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7304e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7473e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1735e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9739e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9011e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5101e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2855e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5972e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3700e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4074e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1005e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1118e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0778e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1911e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1935e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6234e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9197e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2458e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1796e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5679e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0209e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6568e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5800e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5853e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7311e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3814e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1878e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2416e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1826e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3224e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2268e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0397e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3055e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1320e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4538e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0808e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2894e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1013e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5779e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1471e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4594e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7507e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0127e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7304e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4569e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9252e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6697e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6757e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6113e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1321e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8265e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4733e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4259e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6060e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6034e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6967e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9318e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4940e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9727e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0644e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6840e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5252e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3669e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0490e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5992e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7738e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1777e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0422e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9230e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6606e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5395e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4772e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0533e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2194e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1027e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0442e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6472e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0001e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0892e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3417e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0088e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6636e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6766e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1550e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2556e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9537e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8423e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8180e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9863e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0574e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5135e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7567e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5464e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7215e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5395e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0892e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1792e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0551e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8846e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0905e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2099e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9551e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1868e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1320e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0927e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5225e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6243e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5456e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3946e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7811e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4366e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5235e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1896e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7042e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0760e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8250e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6720e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5819e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1018e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2523e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8475e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1432e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0133e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0966e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8682e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1714e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1926e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4905e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6376e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9474e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5187e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9836e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8624e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4245e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9413e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0330e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9430e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5062e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1572e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5968e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7253e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6405e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4236e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5131e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2745e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5286e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5698e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6169e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2851e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4925e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6223e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6152e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2138e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3833e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1459e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8232e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6494e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6567e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8007e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2985e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8725e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3993e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7856e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4167e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1230e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4309e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6926e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8094e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4002e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1420e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9403e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2224e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7393e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3923e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3236e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9020e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1891e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6658e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0382e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4369e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3076e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9342e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2307e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5719e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5386e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9130e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6244e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0706e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7839e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 18---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.806282722513089, 'agreement': 0.2222222222222222, 'direct_attack': 0.1896551724137931, 'undercutter_attack': 0.15384615384615385, 'partial': 0.25}, 'recall': {'support': 0.8235294117647058, 'agreement': 0.08247422680412371, 'direct_attack': 0.3235294117647059, 'undercutter_attack': 0.35294117647058826, 'partial': 0.16279069767441862}, 'f1': {'support': 0.8148148148148147, 'agreement': 0.12030075187969924, 'direct_attack': 0.2391304347826087, 'undercutter_attack': 0.21428571428571433, 'partial': 0.1971830985915493}, 'support': {'support': 374, 'agreement': 97, 'direct_attack': 34, 'undercutter_attack': 34, 'partial': 43}, 'micro_avg': {'precision': 0.5945017182130584, 'recall': 0.5945017182130584, 'f1': 0.5945017182130584, 'support': None}, 'macro_avg': {'precision': 0.32440125419905164, 'recall': 0.3490529848957085, 'f1': 0.31714296287087723, 'support': None}, 'weighted_avg': {'precision': 0.5937016131757543, 'recall': 0.5945017182130584, 'f1': 0.5847163848467888, 'support': None}}
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3842e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4508e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3085e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9158e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7151e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3133e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6991e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1861e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4902e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8596e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9279e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8885e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6796e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8708e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8111e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9988e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6791e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2315e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6354e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5974e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5810e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1286e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3822e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0474e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3064e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7253e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1341e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6307e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5719e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8444e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8293e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2756e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9769e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1783e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6841e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2416e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0696e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0717e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3500e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7899e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5001e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4560e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3514e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3638e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9080e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5468e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2671e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5987e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9790e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1605e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9418e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1634e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9249e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6648e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0391e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6279e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1299e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0611e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5334e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4295e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7605e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5105e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7910e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5679e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1662e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1714e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9884e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8201e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2198e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3419e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7476e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9456e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4629e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7454e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4041e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5577e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8129e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4629e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7781e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4570e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9552e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0811e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5910e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4248e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8059e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7294e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4166e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5386e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6154e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7253e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4404e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5910e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4647e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1583e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6136e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9188e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1895e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8565e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8522e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7440e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0187e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5888e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7363e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7626e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2422e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4217e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6910e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2062e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0168e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6961e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4056e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9216e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7247e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9249e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8833e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7002e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5256e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0866e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7059e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1965e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2774e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2731e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4244e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3846e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2570e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6684e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7410e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4024e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6988e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3660e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7224e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0282e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1199e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6578e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2895e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7908e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9032e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9339e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7272e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5758e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5325e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0899e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6455e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8544e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6157e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2813e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3479e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7977e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2255e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6354e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4660e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2873e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3872e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8384e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1098e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4761e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8444e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1410e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5428e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4511e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3920e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1018e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7575e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0118e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4538e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4154e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4594e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0999e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6182e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5901e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0040e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3600e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8958e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9717e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8544e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8107e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6103e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9464e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8621e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0413e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1762e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5507e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6999e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8180e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8996e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6809e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0052e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3249e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5659e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6371e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9240e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1996e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0960e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3760e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2510e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3270e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3754e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0309e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8742e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2700e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3557e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6108e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5494e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8650e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1165e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2825e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0429e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0130e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8495e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2709e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4630e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9413e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9563e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3669e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0771e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1459e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7566e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4335e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5884e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5789e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2549e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4425e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9584e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6667e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8102e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1737e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0763e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4677e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5579e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2177e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8250e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4348e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8232e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6239e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4154e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2652e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4489e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1784e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2934e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4071e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6921e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0987e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4280e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8816e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7756e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0179e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9030e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4548e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6180e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3410e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6719e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9546e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3146e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9422e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6342e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0741e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8891e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9058e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0935e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4517e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1653e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8883e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7516e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8568e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0680e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7194e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1260e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7202e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4880e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1671e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8465e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4277e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7402e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6364e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1437e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2065e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0261e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8799e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5879e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4261e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1259e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4931e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2259e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6475e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0502e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9370e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0771e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4266e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2095e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7644e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4102e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1165e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1774e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9590e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7043e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3639e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2774e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3206e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7663e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6169e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8803e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9988e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7363e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9926e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2769e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8414e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4170e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9075e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0848e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8924e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8344e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1558e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0468e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5114e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5010e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3067e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5797e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9170e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1229e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5286e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8172e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7974e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3656e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3088e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7607e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4478e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5417e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3608e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2648e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9876e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1187e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6924e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3602e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4863e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5983e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2622e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6455e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0575e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4088e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7911e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4850e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5953e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4620e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4768e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4305e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8830e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6199e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5797e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6576e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4015e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0282e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3125e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3751e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4958e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4502e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9249e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3262e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6095e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1078e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9739e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3146e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9318e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6152e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5673e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7817e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2588e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6122e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9830e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8401e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0430e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7090e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5222e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6070e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2761e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7899e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3431e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9634e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0897e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2504e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4054e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9516e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2401e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4912e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4538e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2540e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9452e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0118e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6524e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8742e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7895e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5782e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4971e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1467e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6095e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9261e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3868e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2670e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7562e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0697e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1589e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0512e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2359e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4283e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9703e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5109e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4651e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3950e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7302e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 19---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7969543147208121, 'agreement': 0.25, 'direct_attack': 0.20930232558139536, 'undercutter_attack': 0.14285714285714285, 'partial': 0.2857142857142857}, 'recall': {'support': 0.839572192513369, 'agreement': 0.10309278350515463, 'direct_attack': 0.2647058823529412, 'undercutter_attack': 0.35294117647058826, 'partial': 0.13953488372093023}, 'f1': {'support': 0.8177083333333333, 'agreement': 0.14598540145985403, 'direct_attack': 0.2337662337662338, 'undercutter_attack': 0.20338983050847456, 'partial': 0.18749999999999997}, 'support': {'support': 374, 'agreement': 97, 'direct_attack': 34, 'undercutter_attack': 34, 'partial': 43}, 'micro_avg': {'precision': 0.6030927835051546, 'recall': 0.6030927835051546, 'f1': 0.6030927835051546, 'support': None}, 'macro_avg': {'precision': 0.3369656137747271, 'recall': 0.33996938371259666, 'f1': 0.31766995981357915, 'support': None}, 'weighted_avg': {'precision': 0.5954811854264747, 'recall': 0.6030927835051546, 'f1': 0.5891912487862759, 'support': None}}
Loss: tensor(2.6070e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8756e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2951e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6009e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7084e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0793e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0551e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1583e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7687e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7266e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8023e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8492e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4790e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5798e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7370e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9041e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8786e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3350e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2619e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9287e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8591e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5075e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9625e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2921e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2800e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4828e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8513e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5927e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1459e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1370e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8928e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7687e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9026e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8885e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1865e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3923e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7469e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2592e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7545e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5200e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7103e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1005e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9279e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6990e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8101e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2048e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5434e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9101e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4305e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5983e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4240e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5706e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8352e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4287e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5680e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6796e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6455e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2755e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2458e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6718e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8453e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6243e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5222e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5802e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2648e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2255e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5153e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2877e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3790e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0061e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4781e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4455e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6718e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2034e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0609e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5546e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9075e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9452e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7535e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8514e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3292e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2075e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3539e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8815e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5866e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6931e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6930e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0650e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7852e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2137e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9249e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4404e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6376e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6228e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4456e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2759e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9736e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6116e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7040e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7060e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9153e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6078e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9512e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6100e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7557e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9158e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0641e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9541e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8414e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8575e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7081e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4690e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5680e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1291e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3821e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0299e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1085e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6697e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3077e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2882e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7683e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5459e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5658e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8730e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9828e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6788e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4768e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4487e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0917e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7622e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5788e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5003e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0896e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1228e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9919e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0021e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7539e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1685e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2830e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1614e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5339e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4526e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8757e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0211e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8807e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1108e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7977e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9923e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6367e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4396e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3616e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3652e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0391e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3111e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9785e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0776e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7839e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5806e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5403e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1943e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8020e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2860e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7618e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3146e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0681e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4925e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3903e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9271e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8032e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7297e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2229e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9543e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9058e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2237e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9443e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9736e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5819e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1212e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9136e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9188e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0369e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5628e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1432e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9059e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8319e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8665e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3146e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2600e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2467e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8444e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7765e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1747e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4511e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4677e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1491e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2339e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2912e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3240e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8678e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9777e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2380e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5871e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4253e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2318e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9404e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5938e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3564e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0814e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7829e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2973e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9364e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5395e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9734e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8838e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7233e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3496e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1952e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1498e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6865e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8422e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3430e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5136e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4586e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0229e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7718e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7847e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7111e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5023e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3276e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3856e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7253e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9724e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9037e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2640e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7916e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4798e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1377e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2738e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4275e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8847e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5650e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0572e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4927e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4558e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2428e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3375e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7525e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1632e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9802e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2652e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5404e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5448e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0957e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5631e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6718e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5836e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8676e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4011e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3730e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2807e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6191e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9819e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7181e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4667e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6848e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4547e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2714e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6003e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7947e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8878e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8271e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6948e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6915e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6083e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5976e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5365e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7039e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5896e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7039e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8371e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9474e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6714e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1826e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3678e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7255e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7531e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8353e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7874e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7220e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0766e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0866e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0443e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5259e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7504e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5962e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5161e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9030e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3606e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1396e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8591e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4638e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8159e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5144e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2557e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7001e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6515e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2034e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8613e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0281e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4750e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5467e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3397e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6406e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0347e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4396e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8314e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9409e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3102e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2188e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1526e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6143e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8444e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9947e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4782e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7202e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8046e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9914e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7817e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1269e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0862e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4487e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6445e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0778e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2761e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6827e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9025e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0442e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7788e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7173e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5083e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7860, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2285e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5797e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4214e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7203e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6227e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4062e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9413e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3431e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3025e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1467e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2743e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2103e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8159e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7715e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1735e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8050e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6164e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8988e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4780e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7860e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7372e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1593e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3033e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6260e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0118e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7374e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0866e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4292e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2034e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6618e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7151e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3327e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9950e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4305e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1138e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8349e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3345e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6956e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8476e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0983e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4186e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5633e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6152e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8061e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3446e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0019e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9249e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7069e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4700e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2211e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1632e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8469e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2385e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9896e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9612e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8030e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7736e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0248e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3647e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9608e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6136e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6567e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9599e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7107e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1593e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8837e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8547e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9045e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2860e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0179e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2190e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9595e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5125e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0953e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0442e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1831e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7410e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3980e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9512e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5736e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5919e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6507e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9422e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4002e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5546e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3489e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5737e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5087e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7350e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8496e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1891e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4231e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0836e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4526e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7614e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9914e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3751e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4980e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0762e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3288e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6799e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4110e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7121e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1065e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4387e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8706e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7713e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8132e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3476e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1925e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9469e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9010e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2679e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1847e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4487e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6576e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4698e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0287e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4362e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7838e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3154e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5546e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7221e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7955e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0274e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8219e-05, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 20---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8, 'agreement': 0.29411764705882354, 'direct_attack': 0.20512820512820512, 'undercutter_attack': 0.13953488372093023, 'partial': 0.14285714285714285}, 'recall': {'support': 0.8235294117647058, 'agreement': 0.15463917525773196, 'direct_attack': 0.23529411764705882, 'undercutter_attack': 0.35294117647058826, 'partial': 0.06976744186046512}, 'f1': {'support': 0.8115942028985507, 'agreement': 0.20270270270270271, 'direct_attack': 0.2191780821917808, 'undercutter_attack': 0.2, 'partial': 0.09374999999999999}, 'support': {'support': 374, 'agreement': 97, 'direct_attack': 34, 'undercutter_attack': 34, 'partial': 43}, 'micro_avg': {'precision': 0.5945017182130584, 'recall': 0.5945017182130584, 'f1': 0.5945017182130584, 'support': None}, 'macro_avg': {'precision': 0.31632757575302034, 'recall': 0.32723426460010996, 'f1': 0.3054449975586068, 'support': None}, 'weighted_avg': {'precision': 0.5937986493615698, 'recall': 0.5945017182130584, 'f1': 0.5867383141593483, 'support': None}}
Loss: tensor(3.9604e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0014e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9421e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8159e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7471e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1286e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4798e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9016e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7841e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9128e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7315e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7008e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5183e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1111e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8552e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0088e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6645e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0645e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8520e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8475e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7138e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4932e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8462e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9729e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5750e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6663e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4054e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5187e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5472e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7977e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7545e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7341e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8113e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1343e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2739e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0499e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7817e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6517e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1571e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6610e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6454e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2904e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2934e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4007e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0881e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8729e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3504e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0120e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9028e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8512e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6790e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1147e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9746e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6294e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5407e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5896e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4266e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1390e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1377e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9698e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6441e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0559e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3560e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2722e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8107e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9703e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6939e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7215e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3950e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4837e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9409e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8535e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8855e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2216e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6312e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5167e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3910e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3267e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1437e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9824e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4159e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2549e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0256e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5909e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9984e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2951e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3072e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7561e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1064e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8840e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5931e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6851e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9612e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3111e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9492e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2255e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1883e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2261e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7184e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4489e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4341e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3228e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4394e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6342e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3245e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9318e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7531e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3202e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3410e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9328e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7454e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2519e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0018e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2450e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9967e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5406e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1590e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0974e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2148e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8340e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4404e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9461e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5585e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1483e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7634e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9318e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8402e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0408e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8234e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8522e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7001e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6756e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9228e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0714e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3686e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1900e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0492e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9469e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8835e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8242e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8967e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6800e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0983e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3206e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5555e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6532e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7213e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5283e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2552e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7311e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7333e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1217e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2300e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2678e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7052e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4242e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7393e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3672e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7288e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4275e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6074e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9954e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4283e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9361e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1437e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3630e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8016e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1895e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0363e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1026e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8090e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0322e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5062e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8141e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7592e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9910e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6562e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9064e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2710e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2356e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7249e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3661e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8151e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5417e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5427e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5255e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2125e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1995e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5659e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3570e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1694e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6948e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9686e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6956e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6083e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8249e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9370e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3941e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6716e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5223e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1727e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1804e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8725e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7420e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4242e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0689e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8061e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7575e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9019e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2125e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7243e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9491e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3043e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7252e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5539e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0234e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8141e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0653e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8986e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2237e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2280e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2514e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2994e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8858e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4547e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7035e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8561e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0066e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7834e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9010e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8462e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2842e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7475e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6312e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8773e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1437e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2480e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1905e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2416e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7674e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1047e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6805e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5704e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8574e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8167e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9592e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5727e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2032e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3024e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2747e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1688e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0170e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2246e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2928e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8210e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2376e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9824e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1247e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5989e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5218e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4166e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6597e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7735e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8948e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7432e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6181e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4780e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6315e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3072e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5668e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0983e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3713e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2731e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4668e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8371e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7000e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9348e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6864e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9128e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5498e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7650e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1684e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1056e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8655e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9723e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6048e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1260e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3266e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8435e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5672e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7302e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9391e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9751e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8171e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6999e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4418e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0502e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3298e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9121e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1013e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9724e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0256e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9186e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1754e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2470e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6546e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8916e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0127e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0745e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1781e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8462e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0577e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0718e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7750e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2657e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9959e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2519e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6857e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3945e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9248e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0342e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8120e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5775e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6848e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5719e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6991e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5417e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1100e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0710e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9793e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9590e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2739e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1328e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3920e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4932e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3458e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7597e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2903e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3639e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8608e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4357e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0581e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2224e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0272e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8009e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4660e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4243e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9716e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2947e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2146e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6960e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1831e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8161e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3004e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6319e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3124e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9491e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9798e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0835e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2800e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9249e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7287e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0563e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0710e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9348e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1656e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8668e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7774e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7341e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5183e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4495e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2064e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3639e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1095e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2592e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2921e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6515e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6960e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1601e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6428e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9772e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5103e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4439e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1437e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0559e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2450e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6009e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5249e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5397e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5455e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3474e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4685e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0733e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8203e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0464e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5425e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1407e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9106e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1222e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6854e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0226e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2761e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8738e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0823e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4750e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0518e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5150e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2973e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7622e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7301e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5700e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8613e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2147e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6194e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7475e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6900e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8704e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5533e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0237e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6243e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8738e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3292e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5404e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4543e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4759e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1186e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8588e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5628e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0805e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3859e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6121e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6102e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1420e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1589e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6658e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3418e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9897e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9590e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4490e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4438e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6857e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7172e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4490e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8867e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6835e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4396e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7008e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9969e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1148e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9312e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2478e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2774e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4789e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2630e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4811e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6158e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4025e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0342e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1515e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4417e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1792e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8461e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8302e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0693e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3932e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2813e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4097e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8042e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2458e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8583e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2721e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7380e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5728e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6022e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4811e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2334e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5689e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5879e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7492e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0148e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5131e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5646e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3965e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5282e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0127e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1441e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4429e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1900e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9736e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1952e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5104e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4911e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7432e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0614e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8734e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4914e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8826e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8773e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3617e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8090e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6385e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5598e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2670e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5706e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4768e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4348e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6909e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7190e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2073e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3738e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2088e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4927e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2717e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6857e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7090e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6472e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9906e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8076e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6939e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2752e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5940e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1441e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5090e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9802e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6350e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2794e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0209e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3781e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1461e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6787e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1374e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6864e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4292e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9139e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7250e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9838e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1792e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4504e-05, device='cuda:0', grad_fn=<DivBackward0>)


		-------------RUN 4-----------
			------------EPOCH 1---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.0, 'agreement': 0.14473684210526316, 'direct_attack': 0.0, 'undercutter_attack': 0.16666666666666666, 'partial': 0.0}, 'recall': {'support': 0.0, 'agreement': 0.946236559139785, 'direct_attack': 0.0, 'undercutter_attack': 0.018867924528301886, 'partial': 0.0}, 'f1': {'support': 0.0, 'agreement': 0.25106990014265335, 'direct_attack': 0.0, 'undercutter_attack': 0.03389830508474576, 'partial': 0.0}, 'support': {'support': 396, 'agreement': 93, 'direct_attack': 44, 'undercutter_attack': 53, 'partial': 28}, 'micro_avg': {'precision': 0.1449511400651466, 'recall': 0.1449511400651466, 'f1': 0.1449511400651466, 'support': None}, 'macro_avg': {'precision': 0.06228070175438596, 'recall': 0.1930208967336174, 'f1': 0.056993641045479826, 'support': None}, 'weighted_avg': {'precision': 0.03630921766958112, 'recall': 0.1449511400651466, 'f1': 0.04095457798494835, 'support': None}}
Loss: tensor(2.5746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8915, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8750, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7885, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7922, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0553, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9601, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0950, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9997, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0569, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7560, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7753, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2955, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6983, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0915, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9797, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9871, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0604, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6904, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6987, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6860, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4693, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6671, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6843, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5751, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6997, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6904, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9769, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6874, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6890, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6826, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4719, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7898, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0641, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4871, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4987, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0965, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9553, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7683, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6983, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7998, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6744, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7956, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6987, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1738, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9553, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8713, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4662, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5654, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1903, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0950, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6739, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3671, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3965, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2744, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5962, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4660, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4798, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6965, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8701, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2753, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6826, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8890, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5927, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4654, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4757, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4798, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4950, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2750, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5739, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7921, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5844, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8744, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5965, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1955, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4374, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6744, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4940, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0750, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7840, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9693, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7757, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1765, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2903, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0926, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8604, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5972, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8374, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2635, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9915, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5929, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2972, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0765, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8730, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1511, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7569, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4950, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4983, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4906, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4874, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5929, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4680, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8785, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7654, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6971, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7926, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4912, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4904, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2873, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4416, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 2---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.9071428571428571, 'agreement': 0.2727272727272727, 'direct_attack': 0.0, 'undercutter_attack': 0.0, 'partial': 0.05517241379310345}, 'recall': {'support': 0.3207070707070707, 'agreement': 0.06451612903225806, 'direct_attack': 0.0, 'undercutter_attack': 0.0, 'partial': 0.8571428571428571}, 'f1': {'support': 0.4738805970149253, 'agreement': 0.10434782608695652, 'direct_attack': 0.0, 'undercutter_attack': 0.0, 'partial': 0.10367170626349892}, 'support': {'support': 396, 'agreement': 93, 'direct_attack': 43, 'undercutter_attack': 54, 'partial': 28}, 'micro_avg': {'precision': 0.255700325732899, 'recall': 0.255700325732899, 'f1': 0.255700325732899, 'support': None}, 'macro_avg': {'precision': 0.2470085087326467, 'recall': 0.2484732113764372, 'f1': 0.13638002587307615, 'support': None}, 'weighted_avg': {'precision': 0.628887679769405, 'recall': 0.255700325732899, 'f1': 0.32616265801201194, 'support': None}}
Loss: tensor(0.6863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9719, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1997, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1705, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5868, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2962, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4751, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8632, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4997, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0987, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9873, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1862, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0714, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3935, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2950, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8915, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2862, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0871, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1994, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2826, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8860, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2921, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5860, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1957, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1569, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9680, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4801, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3950, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0913, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9738, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8427, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6683, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1940, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0929, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1641, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4912, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2683, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0935, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2569, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5955, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5844, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8817, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5713, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2983, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4791, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5978, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1753, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1997, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3481, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5906, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9912, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2903, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6994, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8915, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2987, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8837, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2680, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8753, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1761, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0921, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2927, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8714, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0553, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0757, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8797, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1616, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3955, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6921, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5641, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7972, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7987, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0801, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8769, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2912, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1885, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4852, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2481, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3874, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2874, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3874, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9890, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1560, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0957, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4929, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3511, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3660, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1956, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3601, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4885, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4714, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0753, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7903, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7427, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4940, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2754, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6705, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1773, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7840, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1956, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7730, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6873, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5713, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7921, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7680, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2627, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 3---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.806930693069307, 'agreement': 0.4523809523809524, 'direct_attack': 0.3611111111111111, 'undercutter_attack': 0.12162162162162163, 'partial': 0.375}, 'recall': {'support': 0.8253164556962025, 'agreement': 0.40860215053763443, 'direct_attack': 0.29545454545454547, 'undercutter_attack': 0.16666666666666666, 'partial': 0.21428571428571427}, 'f1': {'support': 0.8160200250312891, 'agreement': 0.4293785310734463, 'direct_attack': 0.325, 'undercutter_attack': 0.140625, 'partial': 0.2727272727272727}, 'support': {'support': 395, 'agreement': 93, 'direct_attack': 44, 'undercutter_attack': 54, 'partial': 28}, 'micro_avg': {'precision': 0.6384364820846905, 'recall': 0.6384364820846905, 'f1': 0.6384364820846905, 'support': None}, 'macro_avg': {'precision': 0.42340887563659846, 'recall': 0.3820651065281527, 'f1': 0.3967501657664016, 'support': None}, 'weighted_avg': {'precision': 0.6413119035672008, 'recall': 0.6384364820846905, 'f1': 0.6380948321067644, 'support': None}}
Loss: tensor(1.2867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7744, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1654, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9929, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4903, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1784, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0753, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7922, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3913, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1852, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5903, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2880, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7862, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1511, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1900, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4641, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6683, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1705, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1987, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8847, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4873, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4784, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5616, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2694, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3801, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1971, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0680, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1641, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0774, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2927, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0654, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0713, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3427, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0852, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2926, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8971, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9926, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6693, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9773, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6705, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5880, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6898, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1904, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0744, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1847, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2753, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3852, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1794, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5903, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0998, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1904, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0972, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0840, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0885, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0740, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2940, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6813, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1774, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0553, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1719, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5739, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8635, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4705, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2774, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4641, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7826, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3604, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0798, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4777, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0769, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0947, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4053, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 4---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7976744186046512, 'agreement': 0.4583333333333333, 'direct_attack': 0.17777777777777778, 'undercutter_attack': 0.5, 'partial': 0.3333333333333333}, 'recall': {'support': 0.8683544303797468, 'agreement': 0.11827956989247312, 'direct_attack': 0.5454545454545454, 'undercutter_attack': 0.037037037037037035, 'partial': 0.25}, 'f1': {'support': 0.8315151515151514, 'agreement': 0.188034188034188, 'direct_attack': 0.2681564245810056, 'undercutter_attack': 0.06896551724137931, 'partial': 0.28571428571428575}, 'support': {'support': 395, 'agreement': 93, 'direct_attack': 44, 'undercutter_attack': 54, 'partial': 28}, 'micro_avg': {'precision': 0.6302931596091205, 'recall': 0.6302931596091205, 'f1': 0.6302931596091205, 'support': None}, 'macro_avg': {'precision': 0.45342377260981914, 'recall': 0.3638251165527605, 'f1': 0.328477113417202, 'support': None}, 'weighted_avg': {'precision': 0.6544982913752324, 'recall': 0.6302931596091205, 'f1': 0.6017242425867476, 'support': None}}
Loss: tensor(0.0403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1769, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3601, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0740, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0660, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4885, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3671, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0705, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2553, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0641, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0783, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2560, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3977, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1738, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0826, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0744, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4862, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1956, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1862, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4956, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1817, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0757, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9777, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7921, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1739, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0641, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2900, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6947, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0705, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2769, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0560, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0719, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3751, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7873, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2005, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 5---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8467532467532467, 'agreement': 0.4835164835164835, 'direct_attack': 0.27710843373493976, 'undercutter_attack': 0.15555555555555556, 'partial': 0.3}, 'recall': {'support': 0.8253164556962025, 'agreement': 0.4731182795698925, 'direct_attack': 0.5227272727272727, 'undercutter_attack': 0.12962962962962962, 'partial': 0.10714285714285714}, 'f1': {'support': 0.8358974358974358, 'agreement': 0.4782608695652174, 'direct_attack': 0.36220472440944884, 'undercutter_attack': 0.1414141414141414, 'partial': 0.15789473684210525}, 'support': {'support': 395, 'agreement': 93, 'direct_attack': 44, 'undercutter_attack': 54, 'partial': 28}, 'micro_avg': {'precision': 0.6563517915309446, 'recall': 0.6563517915309446, 'f1': 0.6563517915309446, 'support': None}, 'macro_avg': {'precision': 0.4125867439120451, 'recall': 0.4115868989531709, 'f1': 0.3951343816256698, 'support': None}, 'weighted_avg': {'precision': 0.6651911018223171, 'recall': 0.6563517915309446, 'f1': 0.6557852967280304, 'support': None}}
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0813, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8652, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1940, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0662, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0765, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0783, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1777, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0720, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0511, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8671, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0915, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6530e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0957, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0862, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0860, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0569, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6773, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1962, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0783, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2662, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4680, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4806, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0427, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4971, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2719, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0935, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9879e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2720, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0940, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 6---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8544973544973545, 'agreement': 0.4166666666666667, 'direct_attack': 0.45454545454545453, 'undercutter_attack': 0.1652892561983471, 'partial': 0.25}, 'recall': {'support': 0.8177215189873418, 'agreement': 0.3763440860215054, 'direct_attack': 0.11363636363636363, 'undercutter_attack': 0.37037037037037035, 'partial': 0.17857142857142858}, 'f1': {'support': 0.8357050452781372, 'agreement': 0.3954802259887006, 'direct_attack': 0.18181818181818182, 'undercutter_attack': 0.2285714285714286, 'partial': 0.20833333333333331}, 'support': {'support': 395, 'agreement': 93, 'direct_attack': 44, 'undercutter_attack': 54, 'partial': 28}, 'micro_avg': {'precision': 0.6319218241042345, 'recall': 0.6319218241042345, 'f1': 0.6319218241042345, 'support': None}, 'macro_avg': {'precision': 0.4281997463815646, 'recall': 0.37132875351740197, 'f1': 0.36998164299795633, 'support': None}, 'weighted_avg': {'precision': 0.6713388841387065, 'recall': 0.6319218241042345, 'f1': 0.640161798661244, 'support': None}}
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0632, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2089e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6439e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4220e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0844, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8153e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0873, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2738, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6742e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0683, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2625e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3170e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4644e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4409e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5368e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8640e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0324e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3472e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 7---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.883008356545961, 'agreement': 0.4891304347826087, 'direct_attack': 0.27906976744186046, 'undercutter_attack': 0.23214285714285715, 'partial': 0.23809523809523808}, 'recall': {'support': 0.8025316455696202, 'agreement': 0.4838709677419355, 'direct_attack': 0.5454545454545454, 'undercutter_attack': 0.24074074074074073, 'partial': 0.17857142857142858}, 'f1': {'support': 0.8408488063660479, 'agreement': 0.4864864864864865, 'direct_attack': 0.36923076923076914, 'undercutter_attack': 0.23636363636363636, 'partial': 0.20408163265306123}, 'support': {'support': 395, 'agreement': 93, 'direct_attack': 44, 'undercutter_attack': 54, 'partial': 28}, 'micro_avg': {'precision': 0.6579804560260586, 'recall': 0.6579804560260586, 'f1': 0.6579804560260586, 'support': None}, 'macro_avg': {'precision': 0.42428933080170506, 'recall': 0.45023386561565404, 'f1': 0.4274022662200002, 'support': None}, 'weighted_avg': {'precision': 0.6934183745769708, 'recall': 0.6579804560260586, 'f1': 0.6711768691887753, 'support': None}}
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0082e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8668e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1555e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2767e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5837, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8892e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5065e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6903e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1353e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8700e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9104e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6639e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5560e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9576e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9173e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1078e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7639e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6014e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2080e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1020e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3379e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9497e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6256e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8791e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1383e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 8---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8531645569620253, 'agreement': 0.6037735849056604, 'direct_attack': 0.27848101265822783, 'undercutter_attack': 0.203125, 'partial': 0.34782608695652173}, 'recall': {'support': 0.851010101010101, 'agreement': 0.34782608695652173, 'direct_attack': 0.5, 'undercutter_attack': 0.24074074074074073, 'partial': 0.2857142857142857}, 'f1': {'support': 0.8520859671302149, 'agreement': 0.4413793103448276, 'direct_attack': 0.35772357723577236, 'undercutter_attack': 0.22033898305084745, 'partial': 0.3137254901960784}, 'support': {'support': 396, 'agreement': 92, 'direct_attack': 44, 'undercutter_attack': 54, 'partial': 28}, 'micro_avg': {'precision': 0.6710097719869706, 'recall': 0.6710097719869706, 'f1': 0.6710097719869706, 'support': None}, 'macro_avg': {'precision': 0.45727404829648705, 'recall': 0.4450582428843298, 'f1': 0.4370506655915481, 'support': None}, 'weighted_avg': {'precision': 0.6943996406515105, 'recall': 0.6710097719869706, 'f1': 0.6750087878565133, 'support': None}}
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5128e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9457e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7368e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5955e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4420e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3311e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9880e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0253e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0152e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9536e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8105e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2464e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3160e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8104e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9840, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9215e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7690e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0868e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7023e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2008e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3007e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2957e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5400e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2916e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1162e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3493e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6146e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9557e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1353e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1393e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7002e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7700e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3824e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0744, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0920e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6276e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9547e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7126e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1838e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5095e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8284e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4409e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7375e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7659e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4138e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5501e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7235e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6167e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1896e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4833e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9900e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1717e-05, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 9---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8455882352941176, 'agreement': 0.6190476190476191, 'direct_attack': 0.42857142857142855, 'undercutter_attack': 0.21348314606741572, 'partial': 0.2631578947368421}, 'recall': {'support': 0.8734177215189873, 'agreement': 0.41935483870967744, 'direct_attack': 0.3409090909090909, 'undercutter_attack': 0.35185185185185186, 'partial': 0.17857142857142858}, 'f1': {'support': 0.8592777085927771, 'agreement': 0.5, 'direct_attack': 0.379746835443038, 'undercutter_attack': 0.26573426573426573, 'partial': 0.2127659574468085}, 'support': {'support': 395, 'agreement': 93, 'direct_attack': 44, 'undercutter_attack': 54, 'partial': 28}, 'micro_avg': {'precision': 0.6889250814332247, 'recall': 0.6889250814332247, 'f1': 0.6889250814332247, 'support': None}, 'macro_avg': {'precision': 0.4739696647434847, 'recall': 0.43282098631220717, 'f1': 0.4435049534433778, 'support': None}, 'weighted_avg': {'precision': 0.6992384939902604, 'recall': 0.6889250814332247, 'f1': 0.68881213812997, 'support': None}}
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3107e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3765e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6449e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7285e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8102e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6579e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6952e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3039e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8506e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8699e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4411e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2987e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6246e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2170e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1526e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1212e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1070e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7085e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0121e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5098e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9091e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2674e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6186e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3976e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7660e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5753e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1989e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7718e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6338e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7136e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1664e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3978e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9627e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6960e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9153e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6548e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9960e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7114e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9376e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7963e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2140e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1685e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9921e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3108e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7266e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6641e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0270e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2634e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4741e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1897e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6793e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5016e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9547e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1120e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 10---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8461538461538461, 'agreement': 0.6037735849056604, 'direct_attack': 0.34545454545454546, 'undercutter_attack': 0.1927710843373494, 'partial': 0.3}, 'recall': {'support': 0.8632911392405064, 'agreement': 0.34408602150537637, 'direct_attack': 0.4318181818181818, 'undercutter_attack': 0.2962962962962963, 'partial': 0.21428571428571427}, 'f1': {'support': 0.8546365914786967, 'agreement': 0.4383561643835617, 'direct_attack': 0.3838383838383838, 'undercutter_attack': 0.23357664233576642, 'partial': 0.25}, 'support': {'support': 395, 'agreement': 93, 'direct_attack': 44, 'undercutter_attack': 54, 'partial': 28}, 'micro_avg': {'precision': 0.6742671009771987, 'recall': 0.6742671009771987, 'f1': 0.6742671009771987, 'support': None}, 'macro_avg': {'precision': 0.4576306121702802, 'recall': 0.4299554706292151, 'f1': 0.43208155640728174, 'support': None}, 'weighted_avg': {'precision': 0.6911911257023005, 'recall': 0.6742671009771987, 'f1': 0.6756524503204833, 'support': None}}
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1048e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8789e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8186e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0739e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9073e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4905e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9749e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4197e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3470e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6658e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5157e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8095e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8587e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9343e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1956e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2040e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8065e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5026e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8962e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0019e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2968e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3570e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4955e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1584e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5620e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8720e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1653e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6061e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5641e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5491e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2252e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9275e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4653e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9444e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7801e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8405e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2794e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1662e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3149e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4699e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4036e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6123e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7354e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0253e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9879e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5034e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8303e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4237e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0633e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4381e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2100e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7953e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3209e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1574e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6933e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7901e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3624e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3500e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8214e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6640e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4387e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9022e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3388e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8202e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4693e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0263e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2603e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3310e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2686e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8901e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6094e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3654e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9789e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3279e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3813e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9101e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8738e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6368e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3903e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1735e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2522e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5582e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2281e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7841e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3016e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5420e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6883e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4531e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3100e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3351e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3067e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8577e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3765e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 11---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8482587064676617, 'agreement': 0.6349206349206349, 'direct_attack': 0.37777777777777777, 'undercutter_attack': 0.1927710843373494, 'partial': 0.23809523809523808}, 'recall': {'support': 0.8632911392405064, 'agreement': 0.43010752688172044, 'direct_attack': 0.38636363636363635, 'undercutter_attack': 0.2962962962962963, 'partial': 0.17857142857142858}, 'f1': {'support': 0.8557089084065244, 'agreement': 0.5128205128205128, 'direct_attack': 0.38202247191011235, 'undercutter_attack': 0.23357664233576642, 'partial': 0.20408163265306123}, 'support': {'support': 395, 'agreement': 93, 'direct_attack': 44, 'undercutter_attack': 54, 'partial': 28}, 'micro_avg': {'precision': 0.6824104234527687, 'recall': 0.6824104234527687, 'f1': 0.6824104234527687, 'support': None}, 'macro_avg': {'precision': 0.4583646883197324, 'recall': 0.4309260054707176, 'f1': 0.4376420336251954, 'support': None}, 'weighted_avg': {'precision': 0.6967562468166957, 'recall': 0.6824104234527687, 'f1': 0.6853969701585454, 'support': None}}
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7338e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8517e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1481e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4793e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6022e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7687e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1847e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1998e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8353e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7317e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8849e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1868e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4971e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2258e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7781e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7363e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4139e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6328e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8020e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8810e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6862e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7305e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9151e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6437e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4448e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4720e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9405e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2402e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1079e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2646e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2976e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6568e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4468e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4572e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8244e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7650e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6367e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5497e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7657e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4411e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7778e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7851e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5498e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5780e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6003e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9706e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1201e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3341e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5649e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4569e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6840e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3473e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9618e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0049e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7618e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9292e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8656e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4551e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3048e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6084e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9062e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1290e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4593e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3755e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7518e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7276e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7446e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4481e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4602e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4429e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8638e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6558e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6104e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1423e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3652e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7982e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5522e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4600e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2155e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8074e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4154e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4811e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0191e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4822e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9345e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8637e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7334e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5692e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4330e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4018e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4668e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8907e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4459e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7799e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7478e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2692e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5702e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5910e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4699e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5014e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9234e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0018e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8417e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0088e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8525e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2532e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6609e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9587e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3009e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5844e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7304e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 12---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8531645569620253, 'agreement': 0.625, 'direct_attack': 0.4444444444444444, 'undercutter_attack': 0.2087912087912088, 'partial': 0.2}, 'recall': {'support': 0.8531645569620253, 'agreement': 0.4838709677419355, 'direct_attack': 0.36363636363636365, 'undercutter_attack': 0.35185185185185186, 'partial': 0.14285714285714285}, 'f1': {'support': 0.8531645569620253, 'agreement': 0.5454545454545454, 'direct_attack': 0.39999999999999997, 'undercutter_attack': 0.26206896551724135, 'partial': 0.16666666666666666}, 'support': {'support': 395, 'agreement': 93, 'direct_attack': 44, 'undercutter_attack': 54, 'partial': 28}, 'micro_avg': {'precision': 0.6856677524429967, 'recall': 0.6856677524429967, 'f1': 0.6856677524429967, 'support': None}, 'macro_avg': {'precision': 0.46628004203953577, 'recall': 0.4390761766098639, 'f1': 0.44547094692009576, 'support': None}, 'weighted_avg': {'precision': 0.7028587635672326, 'recall': 0.6856677524429967, 'f1': 0.6907909829509291, 'support': None}}
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3984e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7457e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7499e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1957e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7345e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5701e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1632e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6479e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8859e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4169e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7294e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0057e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0303e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9386e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5338e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2686e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8072e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5772e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4034e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5366e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7142e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1017e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5076e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2803e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6295e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3790e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4662, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8105e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4421e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4440e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5895e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2735e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0414e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2987e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0036e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3124e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4097e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7811e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9889e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0294e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7636e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6728e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0884e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0200e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1109e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6529e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2782e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2612e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2955e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6221e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4633e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7277e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2016e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4772e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8756e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5023e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0352e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7133e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6152e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1744e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4147e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5561e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0011e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1717e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2635e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4761e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7175e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5541e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3258e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9392e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3403e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7850e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4429e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5913e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6731e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9010e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8050e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6065e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7082e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3673e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2582e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4730e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6155e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3602e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6939e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4922e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2440e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7636e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0879e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5883e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9101e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1020e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3481e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3733e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7124e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4154e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6337e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7151e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1384e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9916e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6328e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9920e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2793e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4911e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2413e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7869e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1251e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8020e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4702e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9507e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4644e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4932e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3582e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0490e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9191e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8800e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6679e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6356e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5068e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2069e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6818e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6982e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1051e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8778e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3094e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7417e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1866e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4572e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1856e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4550e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6379e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5789e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4980e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5910e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8697e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5410e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5901e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3785e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7508e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2513e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3742e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9119e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1109e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4842e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7124e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3863e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1493e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6779e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1934e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0716e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1156e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9606e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6246e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6770e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8941e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7115e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9253e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2653e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3620e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0905e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8084e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3016e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 13---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8422330097087378, 'agreement': 0.6491228070175439, 'direct_attack': 0.34210526315789475, 'undercutter_attack': 0.2261904761904762, 'partial': 0.2608695652173913}, 'recall': {'support': 0.8784810126582279, 'agreement': 0.3978494623655914, 'direct_attack': 0.29545454545454547, 'undercutter_attack': 0.35185185185185186, 'partial': 0.21428571428571427}, 'f1': {'support': 0.8599752168525403, 'agreement': 0.4933333333333334, 'direct_attack': 0.3170731707317074, 'undercutter_attack': 0.2753623188405797, 'partial': 0.23529411764705882}, 'support': {'support': 395, 'agreement': 93, 'direct_attack': 44, 'undercutter_attack': 54, 'partial': 28}, 'micro_avg': {'precision': 0.6872964169381107, 'recall': 0.6872964169381107, 'f1': 0.6872964169381107, 'support': None}, 'macro_avg': {'precision': 0.46410422425840875, 'recall': 0.42758451732318614, 'f1': 0.4362076314810439, 'support': None}, 'weighted_avg': {'precision': 0.6964523208581481, 'recall': 0.6872964169381107, 'f1': 0.6856339261896701, 'support': None}}
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2119e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2453e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9997e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3551e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6217e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4480e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7856e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6243e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5464e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3076e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3500e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8598e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1541e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2706e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5831e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6061e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7297e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3227e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9334e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0374e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0031e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9282e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7235e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6982e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9911e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6589e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6104e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0950e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5407e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4357e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4569e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2322e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4511e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4500e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4581e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6214e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1005e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7021e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3138e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9646e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3583e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8708e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4873e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8941e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1622e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0714e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8838e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8596e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2029e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0088e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0312e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6407e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3025e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6003e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9756e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2915e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3733e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2552e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2614e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8089e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0757e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1822e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1251e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1946e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2743e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9757e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2410e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2564e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6667e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5478e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9261e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8980e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6800e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0769e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5550e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5792e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4742e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3864e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6082e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1217e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3572e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0878e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1149e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2155e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0334e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0512e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3812e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9361e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1966e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2077e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2116e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2419e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4714e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3279e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4825e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7214e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7136e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9210e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0889e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1016e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2179e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3965e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0169e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4569e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0492e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0444e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7243e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1402e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6561e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5286e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2186e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6830e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4127e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3137e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8184e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7567e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7385e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8809e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2119e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3994e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3762e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9945e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8982e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2531e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4398e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8668e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2864e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0706e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6295e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4469e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7224e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3412e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4015e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7678e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4426e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6649e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0776e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5993e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3430e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8052e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3913e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6095e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1726e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7233e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7202e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2017e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0866e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1429e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0706e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5468e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2706e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1623e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0098e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4348e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4914e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5731e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4348e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0101e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5741e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0859e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4853e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3340e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8780e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5982e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6052e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7756e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3773e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8972e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6729e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2471e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9295e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7993e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8437e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7397e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8557e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7930e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5164e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5743e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2813e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0594e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9676e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6649e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3067e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0793e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5326e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4278e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9130e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4045e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3792e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6255e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5438e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9149e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5689e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 14---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.849624060150376, 'agreement': 0.6206896551724138, 'direct_attack': 0.3333333333333333, 'undercutter_attack': 0.20930232558139536, 'partial': 0.29411764705882354}, 'recall': {'support': 0.8582278481012658, 'agreement': 0.3870967741935484, 'direct_attack': 0.4090909090909091, 'undercutter_attack': 0.3333333333333333, 'partial': 0.17857142857142858}, 'f1': {'support': 0.8539042821158691, 'agreement': 0.4768211920529801, 'direct_attack': 0.36734693877551017, 'undercutter_attack': 0.2571428571428572, 'partial': 0.22222222222222224}, 'support': {'support': 395, 'agreement': 93, 'direct_attack': 44, 'undercutter_attack': 54, 'partial': 28}, 'micro_avg': {'precision': 0.6775244299674267, 'recall': 0.6775244299674267, 'f1': 0.6775244299674267, 'support': None}, 'macro_avg': {'precision': 0.4614134042592684, 'recall': 0.43326405865809703, 'f1': 0.4354874984618878, 'support': None}, 'weighted_avg': {'precision': 0.6963028144236841, 'recall': 0.6775244299674267, 'f1': 0.6806315376396652, 'support': None}}
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2095e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2107e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5601e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8435e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3964e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2040e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6900e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4487e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0503e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5447e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6286e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6636e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4884e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0736e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7152e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5881e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6933e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8275e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1331e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9011e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2099e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3461e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4611e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3573e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7992e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2282e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9787e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4266e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4853e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8838e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4621e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6130e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2453e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9364e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9110e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1026e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5546e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0593e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8353e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1643e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2564e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0939e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4418e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7700e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5691e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0233e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5802e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5400e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7257e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0515e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6909e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0896e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8989e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7226e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6615e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3124e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9909e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1271e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9282e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7043e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6831e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5477e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0566e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8401e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3963e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7254e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3297e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9585e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0421e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4668e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8355e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5995e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8679e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9824e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7462e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9010e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1442e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4154e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8354e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5378e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4102e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6225e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0330e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9325e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8185e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0999e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8033e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5480e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7030e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1868e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3700e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9988e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2904e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4782e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7578e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9171e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7043e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6749e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8780e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3136e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8838e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7094e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8777e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6130e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2494e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3016e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7695e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1835e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2310e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1178e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7366e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4905e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2401e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3094e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4841e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7657e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4229e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1269e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2360e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9344e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3639e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1544e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7060e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5409e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9991e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1693e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1714e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8828e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5993e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8172e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2776e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3985e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3700e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7294e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7151e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4369e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0300e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5144e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3470e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8211e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7121e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8314e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2581e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0733e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1623e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9283e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2761e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0187e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1027e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6688e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2398e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6164e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5398e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7657e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7650e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6264e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4435e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3188e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0734e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0187e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1363e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8516e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6658e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7484e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9183e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0502e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9301e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6853e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5962e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6709e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5697e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5343e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8426e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1513e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3139e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0696e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4278e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5670e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8591e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7484e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3301e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5710e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6307e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1139e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4426e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1943e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2858e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5404e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5910e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0878e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6100e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3702e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8383e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7862e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3675e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0806e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9352e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1156e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5077e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8544e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5455e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7475e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3258e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6174e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0594e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3509e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9103e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1217e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0118e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9383e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8243e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8795e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5416e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8395e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6930e-05, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 15---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8498789346246973, 'agreement': 0.625, 'direct_attack': 0.375, 'undercutter_attack': 0.22784810126582278, 'partial': 0.16666666666666666}, 'recall': {'support': 0.8863636363636364, 'agreement': 0.4838709677419355, 'direct_attack': 0.27906976744186046, 'undercutter_attack': 0.3333333333333333, 'partial': 0.10714285714285714}, 'f1': {'support': 0.8677379480840544, 'agreement': 0.5454545454545454, 'direct_attack': 0.31999999999999995, 'undercutter_attack': 0.27067669172932324, 'partial': 0.13043478260869565}, 'support': {'support': 396, 'agreement': 93, 'direct_attack': 43, 'undercutter_attack': 54, 'partial': 28}, 'micro_avg': {'precision': 0.6986970684039088, 'recall': 0.6986970684039088, 'f1': 0.6986970684039088, 'support': None}, 'macro_avg': {'precision': 0.44887874051143734, 'recall': 0.4179561124047245, 'f1': 0.4268607935753237, 'support': None}, 'weighted_avg': {'precision': 0.6966979189680802, 'recall': 0.6986970684039088, 'f1': 0.6944303182980216, 'support': None}}
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9725e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7051e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9128e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0433e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0301e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0334e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0744e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8234e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4672e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8211e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7717e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3107e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3548e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0724e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8301e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3542e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2670e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3245e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5274e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9067e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0222e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0848e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4583e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5339e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9201e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9575e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3634e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9988e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4932e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1180e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4599e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1473e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3068e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1026e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5398e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4801e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8280e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9325e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3647e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3855e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8838e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3033e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5730e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3410e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5537e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2292e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6822e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5497e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9019e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9425e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8133e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6839e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6375e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2208e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4402e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5608e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3037e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6788e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9858e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7082e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7708e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3639e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9284e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2056e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7977e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6428e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8323e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5853e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7907e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5740e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3942e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3124e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4904e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3803e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0099e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4238e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4525e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0432e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4871e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1251e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5244e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7787e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0131e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1018e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0905e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4651e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9083e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1897e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1225e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3612e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7765e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8907e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5961e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4529e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9694e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2059e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3300e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6933e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3025e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5842e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6709e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6113e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6939e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8141e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8090e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8734e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9467e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2753e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9621e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1976e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1974e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1619e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2088e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1462e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4348e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7233e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2329e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9828e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1693e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9090e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3124e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0748e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9628e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0157e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8885e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1723e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0127e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4438e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3593e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7557e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1238e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8253e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3769e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7038e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3309e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4995e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7757e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9333e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0109e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5154e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7598e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7990e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7799e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7696e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1834e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4309e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2904e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2298e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2116e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1013e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5046e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5992e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7769e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1671e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8492e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3215e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1080e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2095e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9131e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6282e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4966e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3997e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3358e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7227e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8011e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3072e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4619e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6731e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1935e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8929e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7405e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1874e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4328e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0646e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2857e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8081e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0391e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5589e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8228e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9634e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0463e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0130e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4417e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4538e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0239e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3754e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3883e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0352e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7232e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6554e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7581e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6126e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8483e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2604e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2744e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8928e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1754e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5005e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7255e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2095e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8090e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7795e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5237e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9828e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9182e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5680e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7626e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7830e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7859e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9798e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9416e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5216e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6809e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6086e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3237e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7739e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8444e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1837e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5637e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9097e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8241e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5954e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7878e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6952e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1331e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0897e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5400e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6969e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6499e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9988e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6485e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5156e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4296e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1520e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7531e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7081e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1952e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5010e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3781e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5367e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4993e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2504e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9061e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4147e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6113e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4066e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5779e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6618e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0837e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1753e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6569e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3790e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5841e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3894e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3783e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3102e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4067e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3730e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3643e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1865e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8937e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1815e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3804e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6043e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0836e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8050e-05, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 16---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.850253807106599, 'agreement': 0.5918367346938775, 'direct_attack': 0.29310344827586204, 'undercutter_attack': 0.2, 'partial': 0.2608695652173913}, 'recall': {'support': 0.8459595959595959, 'agreement': 0.31521739130434784, 'direct_attack': 0.38636363636363635, 'undercutter_attack': 0.3333333333333333, 'partial': 0.21428571428571427}, 'f1': {'support': 0.8481012658227849, 'agreement': 0.41134751773049644, 'direct_attack': 0.33333333333333337, 'undercutter_attack': 0.25, 'partial': 0.23529411764705882}, 'support': {'support': 396, 'agreement': 92, 'direct_attack': 44, 'undercutter_attack': 54, 'partial': 28}, 'micro_avg': {'precision': 0.6596091205211726, 'recall': 0.6596091205211726, 'f1': 0.6596091205211726, 'support': None}, 'macro_avg': {'precision': 0.43921271105874593, 'recall': 0.4190319342493255, 'f1': 0.41561524690673474, 'support': None}, 'weighted_avg': {'precision': 0.6875413465085909, 'recall': 0.6596091205211726, 'f1': 0.665223086087643, 'support': None}}
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2692e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2785e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5092e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6526e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6909e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0969e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8617e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8586e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5498e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0529e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2661e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7787e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0239e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6375e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5001e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2186e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3224e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4547e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8686e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5779e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9476e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8232e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1662e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9378e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1913e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8142e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2300e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4781e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4223e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4644e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2684e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1481e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8184e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3033e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5888e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7432e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2774e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0323e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8202e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7766e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9694e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4486e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6217e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5860e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9606e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0990e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3431e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5520e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8132e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7889e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9361e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8937e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6500e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2307e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7839e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9513e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9828e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9733e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4257e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7666e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2673e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0199e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8081e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1707e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3170e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2125e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8757e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9857e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0684e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9422e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3079e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5425e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2034e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3570e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2401e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5053e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5637e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6818e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2125e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1964e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8737e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7043e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6939e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8940e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5812e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2813e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3950e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7142e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8234e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8344e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6367e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1168e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0490e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0472e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8453e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1013e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0645e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7558e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8591e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7750e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8795e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8877e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3924e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9373e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3345e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0584e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9978e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1099e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8877e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4199e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4791e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9798e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0339e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5014e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0756e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6031e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9214e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6282e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8030e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5580e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5792e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9840e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2168e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8673e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4781e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8401e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7851e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9847e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0828e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8255e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0282e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0406e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3623e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9028e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9616e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1937e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8665e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5852e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0611e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8383e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5345e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7294e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1420e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6788e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3133e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9152e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3681e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7315e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5066e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8531e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7804e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8888e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8098e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0442e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4417e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2934e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9577e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1797e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6708e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4762e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1550e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0088e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8173e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9694e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4357e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2886e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4366e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5676e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0917e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7289e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2561e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6312e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2307e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7990e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4902e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0300e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2631e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2277e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7717e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6358e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2480e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2549e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7121e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2067e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8708e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1532e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4923e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6303e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6639e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5045e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8205e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1027e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7341e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5092e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3639e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8666e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2782e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4438e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3793e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2186e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4783e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5255e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0157e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0594e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2038e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5792e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0169e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6882e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9279e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5252e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9673e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6969e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2564e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2524e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0281e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3428e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1087e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7345e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5637e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6920e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0551e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1096e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3033e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4889e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0209e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5962e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2834e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6744e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1238e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0499e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5126e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6437e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7376e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4931e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6203e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9906e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5304e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0775e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0157e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8051e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1710e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5245e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8825e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3639e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0373e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2497e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6591e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7244e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4508e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2087e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3781e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9854e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4971e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9885e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5098e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9858e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4438e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7303e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4404e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5101e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5745e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2724e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8876e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8950e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6234e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8362e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3430e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3826e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4941e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5131e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9582e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2934e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4752e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0030e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6025e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9566e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5244e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3306e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3188e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6034e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5075e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9140e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8093e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0009e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3400e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1199e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8010e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8786e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5277e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0996e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6636e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4932e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0468e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4430e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9590e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7514e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8098e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8983e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1835e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1221e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5117e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0554e-05, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 17---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8501228501228502, 'agreement': 0.631578947368421, 'direct_attack': 0.3111111111111111, 'undercutter_attack': 0.22093023255813954, 'partial': 0.2631578947368421}, 'recall': {'support': 0.8759493670886076, 'agreement': 0.3870967741935484, 'direct_attack': 0.3181818181818182, 'undercutter_attack': 0.35185185185185186, 'partial': 0.17857142857142858}, 'f1': {'support': 0.8628428927680798, 'agreement': 0.48000000000000004, 'direct_attack': 0.31460674157303375, 'undercutter_attack': 0.27142857142857146, 'partial': 0.2127659574468085}, 'support': {'support': 395, 'agreement': 93, 'direct_attack': 44, 'undercutter_attack': 54, 'partial': 28}, 'micro_avg': {'precision': 0.6840390879478827, 'recall': 0.6840390879478827, 'f1': 0.6840390879478827, 'support': None}, 'macro_avg': {'precision': 0.45538020717947275, 'recall': 0.42233024797745083, 'f1': 0.4283288326432987, 'support': None}, 'weighted_avg': {'precision': 0.6962913850219039, 'recall': 0.6840390879478827, 'f1': 0.6839091676518867, 'support': None}}
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3548e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3077e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6788e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6606e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3314e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3359e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6251e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8544e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8937e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2895e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0445e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8626e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0108e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2822e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5715e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4500e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1089e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2034e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7920e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2164e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3176e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4317e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1692e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9621e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6848e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0909e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8522e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3459e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4594e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8767e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4136e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3762e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0068e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4305e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3639e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0443e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8476e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6445e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4390e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0926e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2376e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5659e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8340e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9698e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6951e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7122e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3963e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5277e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8141e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2825e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9136e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2258e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2670e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9958e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5395e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5608e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3102e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8120e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1381e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9003e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2277e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3989e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2633e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9037e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8029e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5486e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7099e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0036e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4253e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6409e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7226e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5497e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9105e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9897e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8556e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9050e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8183e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5347e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3033e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2382e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7455e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8340e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4105e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1183e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0248e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3994e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8433e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0421e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9906e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9577e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7085e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5621e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0070e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6637e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2246e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4296e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3057e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6103e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1038e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4790e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4616e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0278e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6848e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8409e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8144e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6458e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5400e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9434e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3924e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7455e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0918e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4671e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7072e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5883e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4842e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4075e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9370e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6801e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3461e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5809e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8940e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9667e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6267e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0200e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8525e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5053e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7051e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1208e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6788e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9733e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5640e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2794e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8828e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6666e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1976e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3064e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5296e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9694e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0058e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1935e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8665e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0362e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8235e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3206e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9155e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8271e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9848e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2056e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3829e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7405e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1861e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9373e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9377e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3708e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4036e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8250e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3829e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9737e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1220e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5053e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1271e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2160e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1368e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9806e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0039e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6355e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8401e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0460e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8855e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9856e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5365e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2116e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4572e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0382e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0157e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8645e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2197e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9188e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9959e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8556e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3499e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8111e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5338e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0256e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3232e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9604e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8976e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7000e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8486e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7138e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8409e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7614e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9231e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6709e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4841e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5053e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3730e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0090e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8113e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6738e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8060e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2129e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6891e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9794e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7302e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8241e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2678e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9796e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2116e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6433e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7259e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9763e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3578e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8263e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0892e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4428e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1927e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9318e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7920e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6213e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1571e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6774e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9825e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9058e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5761e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5023e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5585e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3690e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9257e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9584e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2026e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8431e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7095e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1165e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3639e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6143e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7372e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1027e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1498e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6969e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9967e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3617e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1120e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6221e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8288e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2821e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1528e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6796e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5092e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5737e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9165e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7112e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2648e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5092e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3155e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7808e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8098e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9037e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7121e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1684e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8341e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5247e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7929e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9776e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5211e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2695e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7453e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6706e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0075e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9200e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7768e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5525e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3345e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7881e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7886e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4145e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6031e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0702e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7678e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5274e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1280e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5533e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2973e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5135e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7535e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0420e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1835e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4132e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6306e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6334e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6939e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8918e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5334e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1916e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8424e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5382e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3745e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9837e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5992e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1843e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7726e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8971e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5809e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5668e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6771e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2034e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9727e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6082e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8141e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3702e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6982e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9915e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0472e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9776e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5884e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1922e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1550e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3094e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0057e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3046e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4041e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3055e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5987e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6960e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1710e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1753e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6108e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0886e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0583e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1874e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2622e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6398e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 18---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8491484184914841, 'agreement': 0.6557377049180327, 'direct_attack': 0.3488372093023256, 'undercutter_attack': 0.22077922077922077, 'partial': 0.2727272727272727}, 'recall': {'support': 0.8835443037974684, 'agreement': 0.43010752688172044, 'direct_attack': 0.3409090909090909, 'undercutter_attack': 0.3148148148148148, 'partial': 0.21428571428571427}, 'f1': {'support': 0.8660049627791564, 'agreement': 0.5194805194805195, 'direct_attack': 0.3448275862068966, 'undercutter_attack': 0.2595419847328244, 'partial': 0.23999999999999996}, 'support': {'support': 395, 'agreement': 93, 'direct_attack': 44, 'undercutter_attack': 54, 'partial': 28}, 'micro_avg': {'precision': 0.6954397394136808, 'recall': 0.6954397394136808, 'f1': 0.6954397394136808, 'support': None}, 'macro_avg': {'precision': 0.4694459652436672, 'recall': 0.43673229013776177, 'f1': 0.4459710106398793, 'support': None}, 'weighted_avg': {'precision': 0.7024503430443928, 'recall': 0.6954397394136808, 'f1': 0.6942855530588454, 'support': None}}
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6486e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8011e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3933e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4063e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5601e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8393e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8522e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2189e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5274e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3894e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7523e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4682e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7910e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5740e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1847e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3768e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7636e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1683e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8435e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6791e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3866e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2034e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4335e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0919e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3323e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9310e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1151e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4490e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5195e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4002e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1229e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0309e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6610e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0381e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8643e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6870e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9249e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2065e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9106e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7579e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8284e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1693e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6173e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8670e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2519e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8089e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7656e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4532e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8496e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5032e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9493e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9576e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4768e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0589e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8605e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2043e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9807e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7696e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5982e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2915e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5256e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1371e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6628e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4871e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4076e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2709e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1148e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6982e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6727e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4404e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9578e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3760e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1822e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6165e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3410e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8344e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2618e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9370e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0226e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3276e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4651e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6606e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9733e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9210e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9815e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6065e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1891e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2825e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9673e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2579e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8252e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4153e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0109e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4265e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3388e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7925e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8998e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1635e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0827e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3284e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7977e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3357e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6517e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6246e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4260e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5343e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7556e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9815e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3540e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7475e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0096e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8509e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5849e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1148e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7886e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9293e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3220e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4196e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1187e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9110e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9079e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8401e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7067e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1087e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3893e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3317e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1035e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1156e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0089e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1511e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9491e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8361e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4880e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7657e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2467e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7405e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1171e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9348e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4447e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0918e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5749e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5910e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4913e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1856e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8422e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7408e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2682e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9928e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1441e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7977e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3387e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0472e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9434e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3206e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9988e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6524e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3085e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6122e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4699e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5282e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6909e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5153e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1165e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2359e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3872e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8483e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6761e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6039e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8353e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1844e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0725e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3681e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9504e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0256e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9937e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5155e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6221e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9737e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4479e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7637e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5568e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8416e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9590e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1610e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1946e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5198e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6909e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2181e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3452e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9552e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5434e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8032e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3873e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9697e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1972e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6485e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4489e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9909e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4407e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8271e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4586e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9876e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7850e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2807e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8492e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4421e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1775e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4623e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4802e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4638e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9180e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5325e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4199e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5001e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9020e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3348e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2973e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7345e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0550e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0482e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8189e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9703e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2560e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7060e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8353e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9620e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9716e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6532e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6108e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9827e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6372e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1411e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7493e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1936e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6902e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1982e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2582e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5503e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4791e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1359e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3958e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2522e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3094e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1220e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5621e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8591e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2237e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8353e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9170e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4792e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5154e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4679e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2912e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4519e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0389e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4720e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3557e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7638e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1775e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5404e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9261e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8332e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8552e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3215e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3565e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1688e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7281e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5629e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7160e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7017e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2088e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0960e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4283e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4227e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9673e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6374e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1371e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2349e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8284e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1225e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1770e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1411e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6458e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7908e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1423e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8695e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2339e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3314e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6163e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4882e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8565e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8128e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7531e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3691e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8413e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8708e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8007e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4344e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5378e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0868e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4530e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4076e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6828e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0594e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8068e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2643e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0105e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2852e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9657e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2177e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2700e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5139e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4117e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1956e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9655e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1316e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0148e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6485e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3782e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5782e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1714e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9884e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6770e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9755e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1450e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3451e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6911e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6548e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4024e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6489e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4660e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1361e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1904e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8031e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3287e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6221e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4456e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2462e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5641e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8183e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8392e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6441e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4945e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7253e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0079e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6848e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4332e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2774e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3763e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3186e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7584e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2125e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8613e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6193e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9110e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7688e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6840e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7254e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3579e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9620e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6493e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1767e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3015e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1126e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3383e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5654e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2762e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7402e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6956e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8626e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9166e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1922e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5321e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9880e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6791e-05, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 19---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8459657701711492, 'agreement': 0.6338028169014085, 'direct_attack': 0.42857142857142855, 'undercutter_attack': 0.20689655172413793, 'partial': 0.21052631578947367}, 'recall': {'support': 0.8759493670886076, 'agreement': 0.4838709677419355, 'direct_attack': 0.2727272727272727, 'undercutter_attack': 0.3333333333333333, 'partial': 0.14285714285714285}, 'f1': {'support': 0.8606965174129354, 'agreement': 0.5487804878048781, 'direct_attack': 0.33333333333333326, 'undercutter_attack': 0.2553191489361702, 'partial': 0.1702127659574468}, 'support': {'support': 395, 'agreement': 93, 'direct_attack': 44, 'undercutter_attack': 54, 'partial': 28}, 'micro_avg': {'precision': 0.6921824104234527, 'recall': 0.6921824104234527, 'f1': 0.6921824104234527, 'support': None}, 'macro_avg': {'precision': 0.46515257663151954, 'recall': 0.42174761674965844, 'f1': 0.43366845068895277, 'support': None}, 'weighted_avg': {'precision': 0.6987368643025837, 'recall': 0.6921824104234527, 'f1': 0.6909308923452631, 'support': None}}
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2137e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7393e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3630e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5761e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4611e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4435e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3844e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5637e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7462e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0529e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1528e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5365e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9439e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4302e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5467e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1377e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8707e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4413e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0299e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8409e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5338e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2974e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7470e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9009e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4055e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3683e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0725e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7657e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1864e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9767e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2782e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1056e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1453e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6375e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4140e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2073e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4670e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6892e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7696e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0179e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0985, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4632e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3821e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7735e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2401e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0251e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9850e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8689e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1562e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4941e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2155e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8681e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9322e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6939e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9406e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6465e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1995e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4569e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3080e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8864e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3120e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4663e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4919e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8700e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7898e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9473e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4683e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9287e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1548e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7410e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7609e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2293e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6669e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0766e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4490e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0217e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1577e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0209e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1532e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7645e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3518e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4859e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4883e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3254e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5195e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6736e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4054e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7941e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8513e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3881e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6584e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1474e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6930e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9028e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2898e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3753e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7112e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6604e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6375e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5321e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3976e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2307e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2309e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2348e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3288e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7211e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0452e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3163e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6809e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1280e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8440e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4025e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8137e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8458e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5235e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1601e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4184e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2988e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0862e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6052e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9331e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0818e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4413e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2827e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8462e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1188e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9552e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5987e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9370e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6306e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8755e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9430e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2782e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5684e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1177e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8447e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5304e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2791e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5830e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1541e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8742e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8861e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7531e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0914e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4363e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1026e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5537e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9191e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6329e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3858e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8098e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8752e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8864e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1444e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3007e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6689e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6584e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0403e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5761e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9249e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2747e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1789e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7435e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7484e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3541e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5478e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5377e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1107e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7765e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4538e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1758e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6938e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8846e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3064e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6455e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7531e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8522e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9603e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6817e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3330e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8171e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6999e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9391e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5924e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6606e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9794e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3530e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8818e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2731e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2085e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9836e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7717e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6471e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9624e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9162e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8114e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8052e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6113e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9694e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6584e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3875e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3474e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6748e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8777e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5153e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6156e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7657e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2142e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1279e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6255e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2588e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2648e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4902e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8665e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7605e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0715e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5763e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1580e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4019e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2571e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1874e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9898e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2242e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9032e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9262e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3609e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4588e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5434e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4146e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1139e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1368e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6895e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7795e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6174e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2077e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8150e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0672e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3947e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8626e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5954e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8107e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8833e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5444e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6251e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4940e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6627e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8504e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0562e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1167e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9595e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0419e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7129e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1377e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4279e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0421e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0340e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9530e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5662e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0602e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9676e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7436e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5752e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1377e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3647e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4154e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6028e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7501e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8726e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7592e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7008e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4871e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6203e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5274e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4759e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2164e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8230e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9439e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1735e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0127e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7172e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9958e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9181e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9733e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4837e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3447e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9876e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2607e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4495e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4737e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2535e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6152e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0273e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3254e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1139e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7531e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8159e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6031e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8093e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1679e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8002e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4490e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2103e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7989e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9915e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3215e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3768e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3651e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9587e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8204e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2903e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0823e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7614e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5840e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5698e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1497e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3094e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8667e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8090e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6982e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8068e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3388e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0884e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7575e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0127e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9459e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9136e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9768e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1280e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4473e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7985e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9252e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8017e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6416e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2004e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3193e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3055e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0643e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5365e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9551e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1127e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7545e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6921e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6524e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8924e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9270e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4102e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6286e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9227e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1472e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7523e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4230e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5606e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9088e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3085e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8423e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7229e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3708e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5032e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0650e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7630e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1924e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0633e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1802e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6990e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3526e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6502e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2285e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1567e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6917e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3409e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4590e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5979e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4983e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2246e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9618e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4223e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9645e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4184e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0261e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7245e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6433e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8207e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3102e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0159e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3033e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5563e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7311e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0641e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0793e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8362e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4487e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9625e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8894e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1679e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6039e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3479e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8076e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2761e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0862e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6153e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6736e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9863e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2739e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6537e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1233e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8030e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5358e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2094e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6736e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4080e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3198e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4889e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1770e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9742e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9703e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9665e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8431e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7568e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6679e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6833e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7380e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8474e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8696e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6447e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9774e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2357e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5082e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6425e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7493e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4701e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0127e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5070e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1091e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3669e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7751e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9045e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2246e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6826e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2860e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6042e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1762e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2089e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8349e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3111e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2389e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1087e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0612e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9311e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3669e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 20---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.849009900990099, 'agreement': 0.6417910447761194, 'direct_attack': 0.3783783783783784, 'undercutter_attack': 0.20689655172413793, 'partial': 0.2631578947368421}, 'recall': {'support': 0.8661616161616161, 'agreement': 0.4673913043478261, 'direct_attack': 0.3181818181818182, 'undercutter_attack': 0.3333333333333333, 'partial': 0.17857142857142858}, 'f1': {'support': 0.8575, 'agreement': 0.5408805031446541, 'direct_attack': 0.345679012345679, 'undercutter_attack': 0.2553191489361702, 'partial': 0.2127659574468085}, 'support': {'support': 396, 'agreement': 92, 'direct_attack': 44, 'undercutter_attack': 54, 'partial': 28}, 'micro_avg': {'precision': 0.6889250814332247, 'recall': 0.6889250814332247, 'f1': 0.6889250814332247, 'support': None}, 'macro_avg': {'precision': 0.46784675412111537, 'recall': 0.4327279001192045, 'f1': 0.44242892437466236, 'support': None}, 'weighted_avg': {'precision': 0.7010458964264916, 'recall': 0.6889250814332247, 'f1': 0.6910188333608824, 'support': None}}
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7726e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7735e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9461e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9303e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3600e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0290e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6039e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8766e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9460e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9578e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5058e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8535e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7069e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9128e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7886e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7795e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0300e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6415e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7259e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6243e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5507e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7627e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3653e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5304e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6091e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3137e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3639e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4261e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5024e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2406e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0784e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5615e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0166e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5918e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1117e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3390e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7657e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9676e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8175e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2572e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9227e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8708e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6001e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1294e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3565e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7271e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3974e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0174e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4396e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2571e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7191e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8111e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1511e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6619e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1501e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1432e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9954e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9136e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3747e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3881e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5745e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6819e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8323e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1461e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2899e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8240e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0389e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2571e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1350e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4263e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0317e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0483e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9434e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8841e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3478e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8499e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6636e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8427e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1809e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8401e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3738e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1651e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9306e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7752e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0779e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4557e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9910e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0089e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9442e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2765e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9370e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5879e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6852e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5836e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2268e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3133e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5521e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3215e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9579e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3802e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3236e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6623e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9786e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5674e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4157e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4002e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0926e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3136e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8747e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6320e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3609e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3474e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2618e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0692e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7830e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4677e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8007e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1454e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1392e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9648e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2341e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6403e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1861e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8773e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1800e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7505e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5001e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4874e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9075e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0579e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9048e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2833e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1834e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8613e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6705, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9097e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9984e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0334e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2458e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8604e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2238e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8927e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9972e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1060e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2285e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3608e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5337e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2147e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3323e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0391e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3980e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7834e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8351e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7077e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3881e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1792e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1419e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7916e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3276e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6394e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4680e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0602e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5637e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4988e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8979e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6273e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8656e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5304e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5758e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6494e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4701e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1148e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2168e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1619e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5196e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8271e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5546e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3911e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6017e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6017e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7019e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4175e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1904e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3102e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0916e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8182e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5567e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2765e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4859e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6415e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0381e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4549e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4041e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0550e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7198e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8937e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4750e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9523e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2146e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7493e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6697e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8785e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7816e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5368e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5823e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7696e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8855e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2188e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1238e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8059e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2285e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9615e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8828e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2125e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9309e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3720e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2700e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6736e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3678e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6740e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6596e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0221e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6350e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8301e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8379e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5709e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7756e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7069e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0502e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0599e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1635e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7955e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5256e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0805e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1641e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7397e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8250e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9361e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5789e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5698e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3941e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9654e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1740e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2073e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8591e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3802e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4207e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0880e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1309e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3989e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1074e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8202e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5954e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2340e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3224e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4206e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0429e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9491e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1922e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4032e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6169e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0914e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6424e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2908e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6508e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0373e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3630e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4789e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7303e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4858e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3957e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7090e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9158e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1143e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6070e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3367e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2522e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7081e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1191e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8189e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7829e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3375e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8857e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3963e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2673e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4626e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2354e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3611e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8605e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7605e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4833e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1522e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7947e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3003e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5230e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1375e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8674e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2043e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6687e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2389e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0632e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4782e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7402e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1126e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6251e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3358e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9301e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7496e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0503e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4550e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1715e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0078e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7622e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8734e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8132e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4248e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4962e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9015e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2778e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1522e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0529e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6000e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0784e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8353e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6878e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5575e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9530e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0507e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2894e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1780e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8253e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4880e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6155e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9027e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2716e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5347e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0983e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6478e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3040e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1710e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6472e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7968e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5870e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6796e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7244e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7578e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5646e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9416e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9409e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3457e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5139e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3865e-06, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9231e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1627e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9928e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1225e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3417e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9794e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0693e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9706e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3595e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5598e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4886e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8807e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2185e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3678e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0793e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7864e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6882e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1069e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8543e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6593e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1385e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6404e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9279e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4850e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0443e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8051e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2116e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4919e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4800e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1459e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5498e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6290e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0377e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7047e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3799e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5703e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4080e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9389e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7186e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4101e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4286e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3898e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1385e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6307e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6710e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4151e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4539e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3145e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6758e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5075e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7093e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3397e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7969e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8120e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0353e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5893e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4465e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8461e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2570e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6900e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3444e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8657e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6213e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2289e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6260e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4590e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7864e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5382e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4620e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9809e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5154e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7285e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9672e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6578e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8885e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9008e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6327e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1869e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6744e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3793e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8007e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1489e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3072e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8682e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6678e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8500e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6524e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9287e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6532e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2095e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4731e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8319e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9626e-06, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4140e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7107e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1805e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4326e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2752e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4374e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4798e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9875e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6973e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5260e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6620e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8040e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4630e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0347e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1238e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5364e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4227e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4927e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6865e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3810e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7281e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6578e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7069e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9158e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2670e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2048e-06, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1520e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9984e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4564e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1040e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7471e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1621e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6377e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8789e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1441e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8267e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7774e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9577e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5079e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5056e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5378e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0490e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6502e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4586e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5158e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7172e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5023e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1386e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6554e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4952e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3535e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6809e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8272e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0793e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9601e-05, device='cuda:0', grad_fn=<DivBackward0>)


		-------------RUN 5-----------
			------------EPOCH 1---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 1.0, 'agreement': 0.0, 'direct_attack': 0.0, 'undercutter_attack': 0.0, 'partial': 0.07613168724279835}, 'recall': {'support': 0.003003003003003003, 'agreement': 0.0, 'direct_attack': 0.0, 'undercutter_attack': 0.0, 'partial': 1.0}, 'f1': {'support': 0.005988023952095808, 'agreement': 0.0, 'direct_attack': 0.0, 'undercutter_attack': 0.0, 'partial': 0.14149139579349904}, 'support': {'support': 333, 'agreement': 68, 'direct_attack': 27, 'undercutter_attack': 35, 'partial': 37}, 'micro_avg': {'precision': 0.076, 'recall': 0.076, 'f1': 0.076, 'support': None}, 'macro_avg': {'precision': 0.21522633744855968, 'recall': 0.20060060060060061, 'f1': 0.029495883949118968, 'support': None}, 'weighted_avg': {'precision': 0.671633744855967, 'recall': 0.076, 'f1': 0.014458387240814738, 'support': None}}
Loss: tensor(0.7820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1713, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7994, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9977, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8701, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0831, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8777, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6754, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6705, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8738, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9926, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7738, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6783, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1750, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4481, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9511, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7994, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7831, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9826, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3874, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2826, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7965, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4719, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4694, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9604, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6652, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6635, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6739, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9871, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6985, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2898, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1880, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7947, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5774, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0957, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6701, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9694, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1860, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4806, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3956, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6560, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9769, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6769, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8714, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6801, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0817, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7705, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3978, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1900, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4927, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5957, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6903, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6965, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9998, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7601, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7713, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6947, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6777, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4481, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4662, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4847, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4632, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9777, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1873, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9852, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5753, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6972, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2794, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0754, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7739, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4840, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0753, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2831, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5753, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6660, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3987, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0744, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7616, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0906, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8956, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8791, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7794, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4977, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6801, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6868, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6719, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6553, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5871, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7560, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5753, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1903, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9921, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4977, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3769, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5511, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1652, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0817, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4813, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3783, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5950, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3680, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2757, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4871, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5940, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0777, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1553, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3956, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4785, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0935, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5773, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5978, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8632, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6784, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0955, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2817, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2660, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3817, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3908, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 2---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7520215633423181, 'agreement': 0.415929203539823, 'direct_attack': 0.09090909090909091, 'undercutter_attack': 0.5, 'partial': 0.0}, 'recall': {'support': 0.8378378378378378, 'agreement': 0.6911764705882353, 'direct_attack': 0.037037037037037035, 'undercutter_attack': 0.05714285714285714, 'partial': 0.0}, 'f1': {'support': 0.7926136363636365, 'agreement': 0.5193370165745856, 'direct_attack': 0.05263157894736842, 'undercutter_attack': 0.10256410256410256, 'partial': 0.0}, 'support': {'support': 333, 'agreement': 68, 'direct_attack': 27, 'undercutter_attack': 35, 'partial': 37}, 'micro_avg': {'precision': 0.658, 'recall': 0.658, 'f1': 0.658, 'support': None}, 'macro_avg': {'precision': 0.3517719715582464, 'recall': 0.32463884052119346, 'f1': 0.29342926688993864, 'support': None}, 'weighted_avg': {'precision': 0.5973218237764907, 'recall': 0.658, 'f1': 0.6085321085149706, 'support': None}}
Loss: tensor(1.9710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3940, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2813, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3730, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2569, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2553, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7852, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2601, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8817, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5978, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1511, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0791, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5757, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3957, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8826, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5757, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0777, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7739, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8694, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1900, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3754, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7801, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1998, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2852, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2652, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2744, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5671, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8797, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3900, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7601, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1660, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0978, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3998, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8940, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5935, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5844, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7750, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2978, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0826, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0427, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6904, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4705, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1987, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2874, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1713, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5987, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8806, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6962, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3774, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7714, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0826, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6998, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4753, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1885, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1693, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2683, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0972, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4927, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3738, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1813, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8940, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5774, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5785, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6840, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3927, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8783, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5774, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5693, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5956, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7831, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6860, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0761, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6947, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0569, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5985, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1720, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0844, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1817, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2947, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2765, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3601, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1817, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2978, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7738, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1616, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4777, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1860, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6671, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1813, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2739, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1904, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0660, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8560, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4962, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3987, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1769, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0915, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5860, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0890, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5750, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4753, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3903, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0797, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2915, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5885, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0046, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 3---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7761194029850746, 'agreement': 0.6666666666666666, 'direct_attack': 0.15, 'undercutter_attack': 0.10344827586206896, 'partial': 0.2727272727272727}, 'recall': {'support': 0.9369369369369369, 'agreement': 0.17647058823529413, 'direct_attack': 0.2222222222222222, 'undercutter_attack': 0.08571428571428572, 'partial': 0.08108108108108109}, 'f1': {'support': 0.8489795918367348, 'agreement': 0.27906976744186046, 'direct_attack': 0.1791044776119403, 'undercutter_attack': 0.09375, 'partial': 0.125}, 'support': {'support': 333, 'agreement': 68, 'direct_attack': 27, 'undercutter_attack': 35, 'partial': 37}, 'micro_avg': {'precision': 0.672, 'recall': 0.672, 'f1': 0.672, 'support': None}, 'macro_avg': {'precision': 0.39379232364821654, 'recall': 0.300485022837964, 'f1': 0.3051807673781071, 'support': None}, 'weighted_avg': {'precision': 0.6430853865468894, 'recall': 0.672, 'f1': 0.6288580383264032, 'support': None}}
Loss: tensor(0.8645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4481, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0798, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3616, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0904, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1744, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3860, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2785, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0950, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1660, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0962, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4753, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0885, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7900, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1957, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1955, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7785, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4683, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0750, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0660, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2765, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4935, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8632, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0705, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6701, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7912, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3720, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2765, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2915, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8705, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0871, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3773, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4654, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0874, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6641, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0601, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3374, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5739, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5847, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3601, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5900, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0714, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4569, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7654, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2957, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4957, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1714, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1987, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8983, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0957, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3641, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0481, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1720, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1987, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0826, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1765, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0873, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5831, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4511, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0560, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0926, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0977, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0871, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2744, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8769, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1714, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2794, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6965, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6569, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6773, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7796, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4751, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7844, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0680, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4798, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6987, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3847, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2927, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4837, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2998, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6965, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0720, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3880, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0801, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8885, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0906, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5840, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0693, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4652, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0798, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1900, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0871, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0798, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6511, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1752, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 4---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.815028901734104, 'agreement': 0.36363636363636365, 'direct_attack': 0.18181818181818182, 'undercutter_attack': 0.10714285714285714, 'partial': 0.35}, 'recall': {'support': 0.8468468468468469, 'agreement': 0.058823529411764705, 'direct_attack': 0.07407407407407407, 'undercutter_attack': 0.34285714285714286, 'partial': 0.1891891891891892}, 'f1': {'support': 0.8306332842415317, 'agreement': 0.10126582278481011, 'direct_attack': 0.10526315789473684, 'undercutter_attack': 0.16326530612244897, 'partial': 0.24561403508771934}, 'support': {'support': 333, 'agreement': 68, 'direct_attack': 27, 'undercutter_attack': 35, 'partial': 37}, 'micro_avg': {'precision': 0.614, 'recall': 0.614, 'f1': 0.614, 'support': None}, 'macro_avg': {'precision': 0.3635252608663014, 'recall': 0.30235815647580355, 'f1': 0.2892083212262494, 'support': None}, 'weighted_avg': {'precision': 0.6354819758276407, 'recall': 0.614, 'f1': 0.6022621397549728, 'support': None}}
Loss: tensor(0.4290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1971, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8713, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2641, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0481, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3797, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0769, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0890, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0777, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0837, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0720, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0750, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0860, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0922, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5754, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2885, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0616, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1798, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0962, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0880, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0921, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0569, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0481, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5730, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7912, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0871, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4843, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0774, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2693, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0880, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3813, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0604, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2985, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0730, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0890, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0632, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0977, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7906, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3714, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6904, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2654, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4616, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0831, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4843, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7972, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3972, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5947, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0797, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1797, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0904, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0744, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3997, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3817, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9929, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0753, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0693, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4994, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3560, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0560, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3773, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5740, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1719, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4730, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0847, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6720, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4427, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1890, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0604, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5374, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0852, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8957, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6635, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8693, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1635, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4660, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0765, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8843, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1873, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0774, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0409, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 5---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8289855072463768, 'agreement': 0.6363636363636364, 'direct_attack': 0.17857142857142858, 'undercutter_attack': 0.09876543209876543, 'partial': 0.25}, 'recall': {'support': 0.8588588588588588, 'agreement': 0.20588235294117646, 'direct_attack': 0.18518518518518517, 'undercutter_attack': 0.22857142857142856, 'partial': 0.16216216216216217}, 'f1': {'support': 0.8436578171091444, 'agreement': 0.3111111111111111, 'direct_attack': 0.18181818181818182, 'undercutter_attack': 0.13793103448275862, 'partial': 0.19672131147540983}, 'support': {'support': 333, 'agreement': 68, 'direct_attack': 27, 'undercutter_attack': 35, 'partial': 37}, 'micro_avg': {'precision': 0.638, 'recall': 0.638, 'f1': 0.638, 'support': None}, 'macro_avg': {'precision': 0.3985372008560414, 'recall': 0.3281319975437622, 'f1': 0.3342478911993212, 'support': None}, 'weighted_avg': {'precision': 0.6737062397613122, 'recall': 0.638, 'f1': 0.6382179485869567, 'support': None}}
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0885, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6880, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0831, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0671, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3837, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1740, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1616, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0935, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0693, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1777, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2797, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0739, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0817, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0705, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0757, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0860, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2774, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4662, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2694, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0693, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0427, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0794, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0635, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1701, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1750, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0560, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1844, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2950, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0783, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6751, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0852, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0660, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0660, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0873, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2813, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2777, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0972, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0481, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0965, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0393, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 6---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8262295081967214, 'agreement': 0.4, 'direct_attack': 0.1836734693877551, 'undercutter_attack': 0.08163265306122448, 'partial': 0.30434782608695654}, 'recall': {'support': 0.7567567567567568, 'agreement': 0.14705882352941177, 'direct_attack': 0.3333333333333333, 'undercutter_attack': 0.22857142857142856, 'partial': 0.1891891891891892}, 'f1': {'support': 0.7899686520376176, 'agreement': 0.21505376344086022, 'direct_attack': 0.23684210526315788, 'undercutter_attack': 0.12030075187969923, 'partial': 0.23333333333333334}, 'support': {'support': 333, 'agreement': 68, 'direct_attack': 27, 'undercutter_attack': 35, 'partial': 37}, 'micro_avg': {'precision': 0.572, 'recall': 0.572, 'f1': 0.572, 'support': None}, 'macro_avg': {'precision': 0.3591766913465315, 'recall': 0.330981906276024, 'f1': 0.31909972119093366, 'support': None}, 'weighted_avg': {'precision': 0.6428232446506756, 'recall': 0.572, 'f1': 0.5938436270674664, 'support': None}}
Loss: tensor(0.2359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0754, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0654, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0427, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0871, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0784, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0660, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0935, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9862, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2569, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5962, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1754, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0652, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0837, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 7---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7897435897435897, 'agreement': 0.5, 'direct_attack': 0.20689655172413793, 'undercutter_attack': 0.05660377358490566, 'partial': 0.5}, 'recall': {'support': 0.924924924924925, 'agreement': 0.14705882352941177, 'direct_attack': 0.2222222222222222, 'undercutter_attack': 0.08571428571428572, 'partial': 0.10810810810810811}, 'f1': {'support': 0.8520055325034579, 'agreement': 0.22727272727272727, 'direct_attack': 0.2142857142857143, 'undercutter_attack': 0.06818181818181818, 'partial': 0.17777777777777778}, 'support': {'support': 333, 'agreement': 68, 'direct_attack': 27, 'undercutter_attack': 35, 'partial': 37}, 'micro_avg': {'precision': 0.662, 'recall': 0.662, 'f1': 0.662, 'support': None}, 'macro_avg': {'precision': 0.4106487830105266, 'recall': 0.29760567289979056, 'f1': 0.3079047140042991, 'support': None}, 'weighted_avg': {'precision': 0.6461039087132776, 'recall': 0.662, 'f1': 0.6278444869561053, 'support': None}}
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0719, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0683, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0680, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1736e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0784, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1847, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0761, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 8---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8195266272189349, 'agreement': 0.36, 'direct_attack': 0.13793103448275862, 'undercutter_attack': 0.09803921568627451, 'partial': 0.6666666666666666}, 'recall': {'support': 0.8318318318318318, 'agreement': 0.1323529411764706, 'direct_attack': 0.14814814814814814, 'undercutter_attack': 0.2857142857142857, 'partial': 0.10810810810810811}, 'f1': {'support': 0.8256333830104321, 'agreement': 0.19354838709677422, 'direct_attack': 0.14285714285714285, 'undercutter_attack': 0.145985401459854, 'partial': 0.18604651162790697}, 'support': {'support': 333, 'agreement': 68, 'direct_attack': 27, 'undercutter_attack': 35, 'partial': 37}, 'micro_avg': {'precision': 0.608, 'recall': 0.608, 'f1': 0.608, 'support': None}, 'macro_avg': {'precision': 0.4164327088109269, 'recall': 0.30123106299576885, 'f1': 0.29881416521042203, 'support': None}, 'weighted_avg': {'precision': 0.6584090880212523, 'recall': 0.608, 'f1': 0.6078951194070498, 'support': None}}
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9213e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2624e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1556e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7811e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1738e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4038e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9819e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2737e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7035e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0475e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7762e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3148e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2998e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7800e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2776e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9758e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9789e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6519e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1878e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 9---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7989130434782609, 'agreement': 0.4411764705882353, 'direct_attack': 0.17647058823529413, 'undercutter_attack': 0.1038961038961039, 'partial': 0.5}, 'recall': {'support': 0.8828828828828829, 'agreement': 0.22058823529411764, 'direct_attack': 0.1111111111111111, 'undercutter_attack': 0.22857142857142856, 'partial': 0.05405405405405406}, 'f1': {'support': 0.8388017118402282, 'agreement': 0.29411764705882354, 'direct_attack': 0.13636363636363638, 'undercutter_attack': 0.14285714285714288, 'partial': 0.0975609756097561}, 'support': {'support': 333, 'agreement': 68, 'direct_attack': 27, 'undercutter_attack': 35, 'partial': 37}, 'micro_avg': {'precision': 0.644, 'recall': 0.644, 'f1': 0.644, 'support': None}, 'macro_avg': {'precision': 0.4040912412395789, 'recall': 0.29944154238271886, 'f1': 0.3019402227459175, 'support': None}, 'weighted_avg': {'precision': 0.6458782259939548, 'recall': 0.644, 'f1': 0.6232250886443503, 'support': None}}
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0671, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1586e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4593e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0364e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5752e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1968e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6772e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8589e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0828e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8163e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9546e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5249e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7862e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8286e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6740e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2049e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0263e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9275e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3551e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8246e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0082e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6903e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3784e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3340e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7157e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9728e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9073e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4129e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8124e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1989e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3836e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8850e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9678e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5449e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9254e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5620e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7427e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0694, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4895e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0424e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 10---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8242811501597445, 'agreement': 0.3142857142857143, 'direct_attack': 0.17857142857142858, 'undercutter_attack': 0.09009009009009009, 'partial': 0.38461538461538464}, 'recall': {'support': 0.7747747747747747, 'agreement': 0.16176470588235295, 'direct_attack': 0.18518518518518517, 'undercutter_attack': 0.2857142857142857, 'partial': 0.13513513513513514}, 'f1': {'support': 0.7987616099071208, 'agreement': 0.21359223300970875, 'direct_attack': 0.18181818181818182, 'undercutter_attack': 0.13698630136986303, 'partial': 0.2}, 'support': {'support': 333, 'agreement': 68, 'direct_attack': 27, 'undercutter_attack': 35, 'partial': 37}, 'micro_avg': {'precision': 0.578, 'recall': 0.578, 'f1': 0.578, 'support': None}, 'macro_avg': {'precision': 0.3583687535444724, 'recall': 0.3085148173383467, 'f1': 0.3062316652209749, 'support': None}, 'weighted_avg': {'precision': 0.6361248050599488, 'recall': 0.578, 'f1': 0.595230998801535, 'support': None}}
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5420e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2928e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4996e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7569e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2623e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9960e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1041e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2604e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1101e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0857e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4401e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0292e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3963e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3261e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2604e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6076e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7932e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2925e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9052e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3887e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3906e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4109e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4784e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1929e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0627e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1090e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5822e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3221e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8972e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6337e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0566e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8740e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8135e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4875e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7436e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6873e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9517e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4993e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5976e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9970e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4915e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9122e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4893e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6479e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4653e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0566e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9921e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9355e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5703e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0243e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3614e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3058e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1615e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4763e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2261e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7506e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1623e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5552e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6267e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4250e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2958e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2765e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0082e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6610e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2068e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6137e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9607e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9003e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3603e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9940e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9325e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4572e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9516e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0445e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5135e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3351e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1009e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9555e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8628e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6793e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6961e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2080e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 11---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8163265306122449, 'agreement': 0.391304347826087, 'direct_attack': 0.17857142857142858, 'undercutter_attack': 0.07526881720430108, 'partial': 0.46153846153846156}, 'recall': {'support': 0.8408408408408409, 'agreement': 0.1323529411764706, 'direct_attack': 0.18518518518518517, 'undercutter_attack': 0.2, 'partial': 0.16216216216216217}, 'f1': {'support': 0.8284023668639052, 'agreement': 0.1978021978021978, 'direct_attack': 0.18181818181818182, 'undercutter_attack': 0.109375, 'partial': 0.24}, 'support': {'support': 333, 'agreement': 68, 'direct_attack': 27, 'undercutter_attack': 35, 'partial': 37}, 'micro_avg': {'precision': 0.614, 'recall': 0.614, 'f1': 0.614, 'support': None}, 'macro_avg': {'precision': 0.38460191715050457, 'recall': 0.30410822587293174, 'f1': 0.311479549296857, 'support': None}, 'weighted_avg': {'precision': 0.6459563811931073, 'recall': 0.614, 'f1': 0.6138515070506416, 'support': None}}
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6589e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6025e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8265e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4783e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1008e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5954e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1463e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7415e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0533e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3915, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4894e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4602e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3693e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3167e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8608e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5480e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7196e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7215e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2350e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0100e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7901e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5882e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5125e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9011e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9142e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0918e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8679e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4530e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1735e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3491e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4563e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1181e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2120e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5408e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9548e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9758e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6984e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1230e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2038e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5461e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5229e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1242e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4289e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7436e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9149e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9779e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0869e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4490e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3048e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0848e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6589e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1139e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5370e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5147e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3533e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7499e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6954e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8659e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6589e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2280e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8677e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4380e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5598e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5712e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9577e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9365e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6449e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0935, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5722e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2170e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1947e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6588e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1402e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4017e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1565e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9596e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7224e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3512e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7557e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1057e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5669e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2180e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7778e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2756e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3279e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5862e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0676e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2268e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0778e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0646e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7618e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2401e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9607e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2946e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8232e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8547e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2342e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9534e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0212e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2906e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9688e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1566e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7699e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2262e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3703e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6204e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 12---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8192419825072886, 'agreement': 0.36, 'direct_attack': 0.16, 'undercutter_attack': 0.09278350515463918, 'partial': 0.6}, 'recall': {'support': 0.8438438438438438, 'agreement': 0.1323529411764706, 'direct_attack': 0.14814814814814814, 'undercutter_attack': 0.2571428571428571, 'partial': 0.16216216216216217}, 'f1': {'support': 0.831360946745562, 'agreement': 0.19354838709677422, 'direct_attack': 0.15384615384615383, 'undercutter_attack': 0.13636363636363635, 'partial': 0.25531914893617025}, 'support': {'support': 333, 'agreement': 68, 'direct_attack': 27, 'undercutter_attack': 35, 'partial': 37}, 'micro_avg': {'precision': 0.618, 'recall': 0.618, 'f1': 0.618, 'support': None}, 'macro_avg': {'precision': 0.4064050975323855, 'recall': 0.30872999049469635, 'f1': 0.3140876545976593, 'support': None}, 'weighted_avg': {'precision': 0.654110005710679, 'recall': 0.618, 'f1': 0.616755735052129, 'support': None}}
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4460e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1360e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3369e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8456e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6467e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7852e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1554e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0707e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9858e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4693e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2350e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5450e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8941e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5970e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5431e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8465e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2220e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0754e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5794e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6883e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0748e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6549e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4683e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1190e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6581e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8537e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1868e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5468e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8574e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5386e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5964e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0575e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8838e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1716e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0363e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5390e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5438e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6964e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2925e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8396e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3279e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5278e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1393e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8041e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3976e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1121e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0727e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2040e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1190e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4784e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7529e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0857e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0754e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8444e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2100e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8980e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7043e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7105e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8386e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4841e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0862, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6064e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6770e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9646e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1465e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3278e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5843e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9767e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5853e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1202e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9708e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9758e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1130e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8950e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6560e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9452e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2270e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1079e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3418e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9906e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4599e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5268e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6490e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8912e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1584e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0829e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1919e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9353e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0545e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3361e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6279e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3926e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1463e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7575e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3967e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0102e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8738e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4491e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9222e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1292e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2613e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1726e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3067e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9858e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6318e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3249e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5348e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9071e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8296e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2613e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4409e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7368e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2834e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1838e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8544e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2966e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9484e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7822e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1856e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4408e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6660e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7236e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5256e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9817e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8256e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1635e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4814e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5974e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3440e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0990e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3328e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6758e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8335e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4139e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8847e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3028e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0414e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4926e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6669e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7830e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5965e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9716e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6770e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8889e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8142e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4077e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 13---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8173913043478261, 'agreement': 0.391304347826087, 'direct_attack': 0.2222222222222222, 'undercutter_attack': 0.0967741935483871, 'partial': 0.5}, 'recall': {'support': 0.8468468468468469, 'agreement': 0.1323529411764706, 'direct_attack': 0.2222222222222222, 'undercutter_attack': 0.2571428571428571, 'partial': 0.16216216216216217}, 'f1': {'support': 0.8318584070796462, 'agreement': 0.1978021978021978, 'direct_attack': 0.2222222222222222, 'undercutter_attack': 0.14062499999999997, 'partial': 0.2448979591836735}, 'support': {'support': 333, 'agreement': 68, 'direct_attack': 27, 'undercutter_attack': 35, 'partial': 37}, 'micro_avg': {'precision': 0.624, 'recall': 0.624, 'f1': 0.624, 'support': None}, 'macro_avg': {'precision': 0.4055384135889045, 'recall': 0.32414540591011176, 'f1': 0.32748115725754795, 'support': None}, 'weighted_avg': {'precision': 0.6533741935483872, 'recall': 0.624, 'f1': 0.6208849969957351, 'support': None}}
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0182e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3391e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9173e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3582e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5205e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2986e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2441e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4418e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0950e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1826e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2050e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5247e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7800e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5137e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1314e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1172e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3724e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1223e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9595e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4956e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7112e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0148e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9222e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4168e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7912e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6043e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2139e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0212e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4893e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7853e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9746e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6358e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9798e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6861e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0109e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1221e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8223e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8950e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4641e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3955e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1623e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3824e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3842e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9664e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4178e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5570e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2262e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8940e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5005e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7821e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8002e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7467e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2240e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5338e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0836e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4157e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7145e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2613e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5611e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1139e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5035e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8059e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1676e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5923e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3402e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3863e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1744e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1129e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1384e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3228e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2543e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8971e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5771e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8998e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1402e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7839e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7739e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8141e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4138e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2775e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8959e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1390e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9958e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3342e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7819e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1139e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2532e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9979e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6137e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9919e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8475e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6790e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4441e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3782e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1302e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0857e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8202e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0342e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7247e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2504e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3643e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5743e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1190e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7971e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0122e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5700e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7759e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8059e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1109e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2825e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6084e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6903e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8731e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2118e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6600e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8205e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3803e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0088e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5420e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5689e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2222e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6962e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0839e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6187e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0412e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9556e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3281e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9254e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7596e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7224e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0663e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1190e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0989e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4772e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3815e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6840e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1222e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7015e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2019e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7869e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8771e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6485e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7064e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0049e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8920e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1464e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8989e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3845e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6688e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0917e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1202e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5326e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7568e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4096e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3035e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7912e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5801e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1463e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5719e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9646e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6439e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9434e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1048e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0757e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2943e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4371e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8093e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4825e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4784e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3107e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7429e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9464e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3249e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0027e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0936e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4217e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5750e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1241e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2463e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4247e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8800e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0999e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2510e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8577e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4123e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6567e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9636e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2410e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0966e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3206e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2458e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4841e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8938e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4076e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9396e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1247e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 14---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8173913043478261, 'agreement': 0.391304347826087, 'direct_attack': 0.2, 'undercutter_attack': 0.09473684210526316, 'partial': 0.5}, 'recall': {'support': 0.8468468468468469, 'agreement': 0.1323529411764706, 'direct_attack': 0.18518518518518517, 'undercutter_attack': 0.2571428571428571, 'partial': 0.16216216216216217}, 'f1': {'support': 0.8318584070796462, 'agreement': 0.1978021978021978, 'direct_attack': 0.1923076923076923, 'undercutter_attack': 0.13846153846153847, 'partial': 0.2448979591836735}, 'support': {'support': 333, 'agreement': 68, 'direct_attack': 27, 'undercutter_attack': 35, 'partial': 37}, 'micro_avg': {'precision': 0.622, 'recall': 0.622, 'f1': 0.622, 'support': None}, 'macro_avg': {'precision': 0.4006864988558353, 'recall': 0.31673799850270434, 'f1': 0.32106555896694966, 'support': None}, 'weighted_avg': {'precision': 0.6520315789473685, 'recall': 0.622, 'f1': 0.6191181700726581, 'support': None}}
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6022e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2289e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9452e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9504e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2453e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2522e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6973e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7577e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3917e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4320e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9785e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6295e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7930e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7598e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3933e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8344e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0423e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3872e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4704e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3733e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5529e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9676e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1927e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6660e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5183e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4599e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2873e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8911e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4653e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1654e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7709e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4487e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1087e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7163e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4914e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7506e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4227e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6226e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5368e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4833e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7457e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1190e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6031e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1169e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6670e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2241e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3885e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4045e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8597e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0272e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7529e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2543e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2854e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3691e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8910e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5468e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6339e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9628e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2492e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9707e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4802e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2367e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4369e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0978e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9434e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5673e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3591e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8416e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0950e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9837e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0936e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8798e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5984e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3127e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6670e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9900e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2955e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2791e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0836e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7297e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3058e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1208e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6528e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0435e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4154e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9540e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4227e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0763e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1292e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0563e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6154e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7043e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4530e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9808e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3794e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5165e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3046e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6809e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7303e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8587e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6286e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6679e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6630e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5508e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3409e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7393e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8211e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0515e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7519e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5037e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4720e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4086e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8515e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1481e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4923e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4870e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0957e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7605e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5244e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1312e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0736e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7860e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2713e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5810e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4522e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8123e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5007e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4081e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8912e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8284e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1765e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7445e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3646e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5921e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1565e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1616e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8698e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7436e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2090e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8335e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6216e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6627e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5095e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2017e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6800e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9636e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7051e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4945e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1362e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1251e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3276e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5780e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7467e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5368e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8647e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4327e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0808e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0163e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2513e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5931e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9422e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6175e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0373e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1169e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8053e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6146e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6510e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0445e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2086e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8347e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0230e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4457e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5116e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3139e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1010e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7435e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6727e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8325e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3088e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5728e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5895e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5395e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8323e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8665e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2311e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5105e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8398e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3258e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7902e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9201e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3509e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0879e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9101e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4036e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9361e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3734e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3864e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0019e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4427e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7559e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8163e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8211e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 15---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8192419825072886, 'agreement': 0.391304347826087, 'direct_attack': 0.20689655172413793, 'undercutter_attack': 0.0967741935483871, 'partial': 0.5}, 'recall': {'support': 0.8438438438438438, 'agreement': 0.1323529411764706, 'direct_attack': 0.2222222222222222, 'undercutter_attack': 0.2571428571428571, 'partial': 0.16216216216216217}, 'f1': {'support': 0.831360946745562, 'agreement': 0.1978021978021978, 'direct_attack': 0.2142857142857143, 'undercutter_attack': 0.14062499999999997, 'partial': 0.2448979591836735}, 'support': {'support': 333, 'agreement': 68, 'direct_attack': 27, 'undercutter_attack': 35, 'partial': 37}, 'micro_avg': {'precision': 0.622, 'recall': 0.622, 'f1': 0.622, 'support': None}, 'macro_avg': {'precision': 0.4028434151211801, 'recall': 0.32354480530951124, 'f1': 0.3257943636034295, 'support': None}, 'weighted_avg': {'precision': 0.6537791589956927, 'recall': 0.622, 'f1': 0.6201251169846635, 'support': None}}
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1502e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1190e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3591e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9119e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2925e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7509e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4539e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5630e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0887e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5145e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7769e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2380e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1935e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2049e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0312e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3439e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6667e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3391e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8850e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4663e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9030e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8929e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5216e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4109e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2754e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3578e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9608e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3358e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4378e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0344e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8920e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8860e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9859e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4620e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2307e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4033e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4330e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5338e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6067e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9848e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4175e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3806e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6116e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1372e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0687e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0049e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5810e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4954e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8888e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5810e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6425e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2867e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1027e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8223e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7969e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4774e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2675e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8562e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4253e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3560e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1656e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6424e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6600e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1876e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2322e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5869e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4478e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4660e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0908e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3612e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6648e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1883e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0342e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9970e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3367e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9032e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6941e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6055e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6943e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3418e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0170e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6122e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5902e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9938e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0886e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3753e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2686e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6973e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3289e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6274e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4218e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3805e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0079e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5801e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3025e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2278e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4290e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2359e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6204e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8535e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2379e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7619e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8232e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1623e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3814e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4811e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5953e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0058e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0292e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5276e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8041e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2955e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1130e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8393e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9595e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1271e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4660e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0172e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1898e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4197e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5983e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9676e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7194e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4460e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4852e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5598e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1594e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4490e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9430e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9707e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6557e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9214e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2065e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0645e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9555e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0311e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9110e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2813e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7779e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3342e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5651e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5045e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2883e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3652e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7557e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4408e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1674e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1351e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4096e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9676e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0112e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1230e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0066e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1390e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3128e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0648e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7951e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1344e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6125e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5005e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7244e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8254e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9443e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0170e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8638e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6757e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2329e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6518e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8366e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8670e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8163e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7163e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3603e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4862e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9576e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7637e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6658e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4128e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9422e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7605e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1098e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4063e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2864e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8032e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3894e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5287e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6105e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1390e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7203e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9383e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4593e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9110e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9062e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5235e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8034e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2292e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2895e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6251e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8850e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0648e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3077e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2631e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9919e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3167e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0294e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0191e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6476e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2624e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4256e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7055e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4500e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4993e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6031e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0495e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7275e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4702e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9482e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8241e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8939e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8032e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8756e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3167e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1491e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6022e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9857e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8549e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7506e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5660e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6103e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8153e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2330e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8294e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1807e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4729e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3963e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6074e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4266e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2904e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8574e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8686e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7324e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1550e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1783e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5953e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8786e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1423e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8526e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3491e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7791e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1503e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2613e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7354e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6628e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1834e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1947e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0918e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1314e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6497e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0375e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5620e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 16---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8192419825072886, 'agreement': 0.391304347826087, 'direct_attack': 0.20689655172413793, 'undercutter_attack': 0.0967741935483871, 'partial': 0.5}, 'recall': {'support': 0.8438438438438438, 'agreement': 0.1323529411764706, 'direct_attack': 0.2222222222222222, 'undercutter_attack': 0.2571428571428571, 'partial': 0.16216216216216217}, 'f1': {'support': 0.831360946745562, 'agreement': 0.1978021978021978, 'direct_attack': 0.2142857142857143, 'undercutter_attack': 0.14062499999999997, 'partial': 0.2448979591836735}, 'support': {'support': 333, 'agreement': 68, 'direct_attack': 27, 'undercutter_attack': 35, 'partial': 37}, 'micro_avg': {'precision': 0.622, 'recall': 0.622, 'f1': 0.622, 'support': None}, 'macro_avg': {'precision': 0.4028434151211801, 'recall': 0.32354480530951124, 'f1': 0.3257943636034295, 'support': None}, 'weighted_avg': {'precision': 0.6537791589956927, 'recall': 0.622, 'f1': 0.6201251169846635, 'support': None}}
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7687e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8495e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2846e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5174e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3025e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3288e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4188e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8678e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3098e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6658e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7173e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9233e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0512e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5546e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7033e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8344e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8717e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2904e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6186e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6720e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7082e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2813e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0373e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3863e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5389e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4036e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2804e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2592e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0754e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3603e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2753e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4283e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3562e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2773e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0709e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9465e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5486e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8665e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8457e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7083e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9657e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5895e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0836e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8063e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1905e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9655e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7008e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7354e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2328e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2492e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6839e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5259e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0485e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4269e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6542e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3281e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6931e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5758e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5317e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7024e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1753e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7696e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5922e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6122e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0677e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8577e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6840e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1632e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5256e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3379e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4318e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0430e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3179e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1222e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7337e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4965e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0014e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8589e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8777e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7112e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8870e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2280e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1087e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9543e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8846e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7891e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7769e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5126e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7599e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5792e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2582e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8211e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6316e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3942e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0635e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9837e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3760e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6234e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5471e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1714e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3306e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7094e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9430e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1069e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7489e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1913e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5244e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2821e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6588e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7043e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2170e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0430e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6285e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6772e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8468e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2683e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1181e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0939e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1199e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8263e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3630e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9428e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8023e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8574e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0708e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1671e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0525e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4135e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4266e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7907e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1316e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1863e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8241e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8596e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9122e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3185e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1450e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6608e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3317e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0554e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4093e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5918e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0784e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1199e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0644e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1189e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0918e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4531e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3785e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5701e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1895e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1956e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8583e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4196e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2281e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3000e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5456e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3238e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7778e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0202e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7990e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5126e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1946e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5439e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5943e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2834e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7018e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5585e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6891e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7990e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0157e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5256e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2086e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2131e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1362e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4822e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0884e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9097e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5555e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6558e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1575e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4992e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1917e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7609e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3289e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6312e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0767e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1571e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6043e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9022e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5307e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6173e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7008e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9050e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6900e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3457e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2946e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7841e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5719e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3288e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6639e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3804e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7294e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0646e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3340e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2095e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8517e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9738e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9021e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0680e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2531e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5335e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5347e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8734e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4197e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2883e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5065e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6658e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0088e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7363e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1187e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8596e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8274e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3450e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9846e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8314e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3086e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2289e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1412e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2674e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8928e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6801e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4368e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8968e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3534e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5853e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4266e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0339e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4781e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4032e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3493e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8183e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9040e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8492e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1726e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7587e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3279e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9494e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5529e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0702e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4039e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2794e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8759e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9342e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4351e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0633e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7931e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3678e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6557e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0442e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3099e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5571e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2882e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2800e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1714e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9624e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5508e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3673e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9019e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4154e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2712e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5014e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3612e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6244e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3158e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6001e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7091e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9746e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3170e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2046e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4106e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0470e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5629e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9945e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8537e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7848e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8885e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2328e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3751e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6584e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5952e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3057e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7324e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7402e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4744e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4175e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4971e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1524e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9837e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6406e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9058e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 17---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8155619596541787, 'agreement': 0.391304347826087, 'direct_attack': 0.2222222222222222, 'undercutter_attack': 0.08791208791208792, 'partial': 0.5}, 'recall': {'support': 0.8498498498498499, 'agreement': 0.1323529411764706, 'direct_attack': 0.2222222222222222, 'undercutter_attack': 0.22857142857142856, 'partial': 0.16216216216216217}, 'f1': {'support': 0.8323529411764707, 'agreement': 0.1978021978021978, 'direct_attack': 0.2222222222222222, 'undercutter_attack': 0.126984126984127, 'partial': 0.2448979591836735}, 'support': {'support': 333, 'agreement': 68, 'direct_attack': 27, 'undercutter_attack': 35, 'partial': 37}, 'micro_avg': {'precision': 0.624, 'recall': 0.624, 'f1': 0.624, 'support': None}, 'macro_avg': {'precision': 0.40340012352291515, 'recall': 0.3190317207964267, 'f1': 0.3248518894737382, 'support': None}, 'weighted_avg': {'precision': 0.6515355025878771, 'recall': 0.624, 'f1': 0.6202594955931091, 'support': None}}
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6930e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1090e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8629e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5425e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6494e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1011e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6282e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6303e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0745e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9925e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4793e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4481e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7129e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8635e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2542e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7742e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1377e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4955e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3221e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7601e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5791e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3673e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1330e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6303e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9758e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2083e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9906e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4983e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0319e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6701e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6827e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8768e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4117e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3762e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6861e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2703e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4971e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7272e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1229e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7218e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7838e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7726e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5032e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6122e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9292e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5244e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0597e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5797e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1844e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0806e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4854e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8596e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6294e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5790e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5023e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1926e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6568e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2449e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3146e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2332e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0996e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3228e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1898e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9092e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2276e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8726e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9815e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1632e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8332e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9425e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6788e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3651e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1784e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9343e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6416e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3552e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6458e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7908e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2752e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6317e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5297e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0715e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8036e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2884e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4572e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1057e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4864e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7164e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5740e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6808e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1407e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5029e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9974e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0908e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3963e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4763e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5124e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8084e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2855e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2413e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0957e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6667e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8098e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8163e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2816e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5601e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4893e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7436e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6113e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7173e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7769e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5679e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6809e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4517e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2108e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3812e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8234e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6372e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1047e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6022e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1092e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6952e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8998e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6772e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0533e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1165e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6428e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0405e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0626e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2419e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4641e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1511e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0654e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3279e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6455e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2492e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3548e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3659e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3160e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1844e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4568e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7103e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6883e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8444e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8810e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9340e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1356e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5770e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8716e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2753e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0829e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2675e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5641e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0918e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8150e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9361e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8504e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2904e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4015e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7193e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7539e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5657e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4893e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6504e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8007e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0353e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1035e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2623e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2964e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4983e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6636e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8726e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5085e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1853e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2328e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6424e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2532e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3480e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4508e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5486e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1381e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7185e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1290e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9703e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4802e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5447e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1645e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5891e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0218e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4677e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3996e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2237e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7181e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5347e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1230e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3664e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9664e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9041e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3812e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6667e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0633e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2552e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8144e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1917e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2451e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1027e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6398e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3348e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5004e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2774e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4911e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9461e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0888e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7254e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2268e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1562e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7385e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0027e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1017e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4036e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4633e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1368e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9113e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5265e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7627e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8371e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9434e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3227e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4923e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1716e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1674e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8332e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2490e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5810e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0179e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8180e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7765e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2471e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0157e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5468e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4690e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2480e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3904e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7781e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7657e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8536e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7102e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6218e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9646e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2795e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8788e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2158e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0636e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4541e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6131e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1946e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1503e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0443e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4063e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4855e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1796e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4184e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1755e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6666e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7041e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2189e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0999e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1150e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2863e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6286e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2351e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8795e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3609e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6421e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4318e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7951e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6207e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1472e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1065e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2034e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9191e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6576e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5430e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3330e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9891e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3163e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9394e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3894e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6597e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4548e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5395e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5157e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8968e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1250e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8855e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7053e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3046e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4396e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0866e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7657e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2540e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1625e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5973e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6455e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0888e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7242e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4841e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7523e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8677e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2231e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4269e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0465e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6424e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2824e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0523e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8880e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3924e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6433e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9292e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2551e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1977e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7808e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7739e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5632e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0342e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3227e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3193e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7163e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9309e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7045e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5213e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5550e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8655e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7650e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3785e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7266e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5043e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6307e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9041e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6712e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8608e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6619e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5282e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7860e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 18---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8228571428571428, 'agreement': 0.5, 'direct_attack': 0.21428571428571427, 'undercutter_attack': 0.09782608695652174, 'partial': 0.5}, 'recall': {'support': 0.8648648648648649, 'agreement': 0.1323529411764706, 'direct_attack': 0.2222222222222222, 'undercutter_attack': 0.2571428571428571, 'partial': 0.16216216216216217}, 'f1': {'support': 0.8433382137628112, 'agreement': 0.20930232558139536, 'direct_attack': 0.21818181818181817, 'undercutter_attack': 0.14173228346456693, 'partial': 0.2448979591836735}, 'support': {'support': 333, 'agreement': 68, 'direct_attack': 27, 'undercutter_attack': 35, 'partial': 37}, 'micro_avg': {'precision': 0.636, 'recall': 0.636, 'f1': 0.636, 'support': None}, 'macro_avg': {'precision': 0.42699378881987576, 'recall': 0.32774900951371544, 'f1': 0.331490520034853, 'support': None}, 'weighted_avg': {'precision': 0.6714421118012421, 'recall': 0.636, 'f1': 0.6299538936490316, 'support': None}}
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6009e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7454e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9058e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2258e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1241e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2421e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8290e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2280e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1913e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2722e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9806e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7372e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4556e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7365e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5123e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6125e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6547e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4621e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6933e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6355e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4854e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4501e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8604e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4084e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8589e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9767e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4385e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3274e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9404e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7977e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7709e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2228e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0581e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1601e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5467e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5710e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8125e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7830e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1180e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9897e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3276e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1065e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8132e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3760e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9446e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0572e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0036e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9594e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4157e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3647e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2713e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2035e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6406e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6719e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1995e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3168e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5668e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0806e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5758e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3179e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8344e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9634e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6872e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5252e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6073e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0036e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7031e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3248e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7862e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2588e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6636e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9474e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6273e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2985e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5943e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4071e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6658e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4798e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5758e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5101e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7793e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3418e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3267e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6394e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3811e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7771e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4296e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5456e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2709e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1904e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0884e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0445e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5858e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6130e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2695e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3167e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9452e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3730e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8898e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7302e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8596e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7878e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1411e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5304e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9824e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0451e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0118e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1338e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5438e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2971e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3639e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5215e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8885e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9612e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7404e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8353e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4341e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9374e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9716e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3631e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8976e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2685e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6638e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6477e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5425e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6606e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6782e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1217e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2519e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7546e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7328e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0066e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4032e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6658e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2767e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3275e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0099e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8648e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6418e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0987e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0252e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8699e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4748e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0658e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1463e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8937e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5114e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5797e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9827e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9301e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2398e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7629e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6398e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2918e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6930e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5416e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7493e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4650e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5386e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2581e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7099e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1351e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3621e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3449e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6784e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3066e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3984e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4314e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7990e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8604e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5239e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8819e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3456e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1543e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2731e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2004e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9482e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2246e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3971e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0523e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0430e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0784e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7587e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2671e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9763e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2800e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4387e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1141e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9262e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5728e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2752e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4974e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9007e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0624e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3197e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5244e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5274e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2942e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1040e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2398e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2298e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8894e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8859e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5589e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0157e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8534e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4159e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6606e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7856e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4439e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6334e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8747e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6093e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2250e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1654e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0533e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4630e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1351e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0066e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0118e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3584e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9343e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7255e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0128e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9747e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1459e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3304e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3561e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8020e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0708e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0896e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6819e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4061e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0805e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5728e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7687e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7523e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2086e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5629e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2216e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1636e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4307e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4872e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8522e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3449e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1180e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7747e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4914e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5758e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9854e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5144e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9200e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1896e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6173e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4620e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9807e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9915e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0021e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1704e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2837e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9181e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1934e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5113e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5256e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4283e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9068e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8565e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1552e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4236e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4510e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3186e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9072e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1917e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7142e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1493e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0536e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8371e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9121e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2744e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8371e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4608e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8989e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0377e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5356e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1656e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9637e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1783e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1359e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0443e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8583e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1381e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3489e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2077e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8855e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7133e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2282e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8332e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9847e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3146e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5291e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1011e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3076e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4608e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1169e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4451e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9115e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3782e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7557e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7902e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3972e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2964e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4296e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3137e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1861e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2573e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9827e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4401e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0382e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3126e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3228e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4722e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3166e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9815e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4519e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2520e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8052e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2712e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6688e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3115e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6083e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8414e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0919e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0996e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8976e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3024e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0512e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6597e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9848e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3267e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1171e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4575e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1853e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8181e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6857e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4448e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7143e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5659e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5227e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6177e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5494e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5329e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8797e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7408e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4508e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8877e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9945e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1794e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5668e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4550e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6661e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2480e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9001e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0024e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6545e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1941e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9655e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6191e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6016e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8864e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2612e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1282e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2588e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8001e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8828e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5528e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9534e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3833e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4620e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3620e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1814e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3491e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0693e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9097e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5347e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9556e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0914e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8163e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8597e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6848e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2852e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5208e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5458e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8728e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3621e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2610e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4590e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2791e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7649e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3859e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0048e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0278e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8906e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3412e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0745e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7129e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0957e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1835e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8092e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3591e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3611e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4335e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6681e-05, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 19---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8059299191374663, 'agreement': 0.5294117647058824, 'direct_attack': 0.14285714285714285, 'undercutter_attack': 0.08860759493670886, 'partial': 0.5}, 'recall': {'support': 0.8978978978978979, 'agreement': 0.1323529411764706, 'direct_attack': 0.1111111111111111, 'undercutter_attack': 0.2, 'partial': 0.16216216216216217}, 'f1': {'support': 0.849431818181818, 'agreement': 0.21176470588235297, 'direct_attack': 0.125, 'undercutter_attack': 0.12280701754385966, 'partial': 0.2448979591836735}, 'support': {'support': 333, 'agreement': 68, 'direct_attack': 27, 'undercutter_attack': 35, 'partial': 37}, 'micro_avg': {'precision': 0.648, 'recall': 0.648, 'f1': 0.648, 'support': None}, 'macro_avg': {'precision': 0.41336128432744007, 'recall': 0.3007048224695284, 'f1': 0.3107803001583408, 'support': None}, 'weighted_avg': {'precision': 0.6596661435054079, 'recall': 0.648, 'f1': 0.6279905311167526, 'support': None}}
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5235e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9544e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7475e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9060e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3647e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7168e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8650e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5486e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9937e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4066e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2906, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9885e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7516e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1886e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9984e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8409e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2305e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3661e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4721e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7029e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7921e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5441e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5849e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6720e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4850e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3003e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6143e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6796e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0884e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0129e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8353e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2406e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4159e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5104e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0429e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6110e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0375e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5076e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2995e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9508e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6275e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8533e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3215e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1420e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9685e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4175e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1038e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1159e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5648e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2519e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9755e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0766e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4175e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8635e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6073e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0278e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1775e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4319e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8535e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5499e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0222e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4327e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4396e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5646e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5464e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9361e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4790e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3491e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9179e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9454e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0905e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3418e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1020e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6091e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5395e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8604e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3479e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7462e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2761e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2410e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7062e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4941e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1407e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5416e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3146e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8673e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9464e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9361e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1441e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3018e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6266e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2129e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9854e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7666e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0830e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0105e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5801e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9846e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2112e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0663e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3017e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3681e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6303e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8195e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8707e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8561e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6899e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4850e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0051e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5622e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9837e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0713e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3475e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6115e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7808e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6546e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6978e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5767e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3146e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4245e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6540e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4471e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8423e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2207e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7834e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7736e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9772e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2592e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9858e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2362e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4993e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3348e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9171e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4668e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6083e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7209e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0472e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5252e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8016e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4643e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0957e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2720e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8280e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1451e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2857e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1138e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3155e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7834e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2258e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6780e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6061e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0097e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8492e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3124e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6719e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3814e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1277e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4751e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1018e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4132e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4305e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4002e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5740e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1013e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5265e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5356e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0875e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5804e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0218e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1976e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9863e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7585e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5555e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0433e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8980e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6939e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6677e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8161e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6684e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4366e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8302e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9627e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2904e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6615e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3367e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5307e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5282e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1211e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6221e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2370e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1665e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9648e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6675e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7323e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9249e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6167e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3672e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8924e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9906e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5646e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6827e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9914e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3821e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5456e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3612e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1368e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9469e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1580e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4277e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4418e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7035e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3826e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8387e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6286e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3033e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9491e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7908e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4026e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1108e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5435e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9503e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2186e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1683e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0724e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9794e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5274e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1502e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4002e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1230e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2053e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8098e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1363e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8041e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3345e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1805e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2803e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2337e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9545e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7518e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2011e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2647e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3550e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8552e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9080e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0187e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9604e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6255e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6237e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6597e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2427e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6070e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5952e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3479e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5922e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7484e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1150e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2016e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9556e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6679e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2406e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8676e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1147e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8029e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9664e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8189e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4850e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1854e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8004e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2419e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3116e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9555e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6463e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7969e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2359e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3130e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1420e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0151e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5137e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4283e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8050e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2025e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5840e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9446e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6609e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8826e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3176e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8371e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9970e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0070e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9674e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8302e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7220e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5477e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8492e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9577e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3076e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2467e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1477e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8483e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4629e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2078e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7731e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8181e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8742e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6377e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1999e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3518e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8059e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9128e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8189e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4712e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6394e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2034e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3556e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5549e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4880e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2925e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1675e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9037e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4798e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9213e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1223e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1368e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9544e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7176e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8430e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5550e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2216e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0969e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4872e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5965e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4085e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2367e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7244e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6113e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2442e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8144e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3207e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6727e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1260e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1198e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6827e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1459e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1117e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4000e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4974e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6100e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9815e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0377e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0330e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9158e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9543e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2230e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0854e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6437e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7523e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7107e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9779e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8957e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2339e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4195e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8265e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2943e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9927e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3418e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1723e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5312e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1762e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4296e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8989e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2095e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4983e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4846e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1891e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7224e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9218e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1526e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4821e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8959e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9918e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6917e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9435e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4971e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1031e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5818e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2631e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7785e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6954e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9542e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5408e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7151e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9252e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9621e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6788e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5616e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9382e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9897e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7224e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3185e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0551e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4810e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0568e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1632e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2319e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9724e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4862e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3546e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9984e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7212e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4828e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8522e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3167e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0231e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4438e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3349e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2045e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9543e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3803e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5649e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5557e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1943e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2330e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0438e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8880e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5276e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2679e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0685e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3215e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2951e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5001e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2648e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5680e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7797e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4793e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6313e-05, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 20---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8284023668639053, 'agreement': 0.4166666666666667, 'direct_attack': 0.21875, 'undercutter_attack': 0.09574468085106383, 'partial': 0.5}, 'recall': {'support': 0.8408408408408409, 'agreement': 0.14705882352941177, 'direct_attack': 0.25925925925925924, 'undercutter_attack': 0.2571428571428571, 'partial': 0.16216216216216217}, 'f1': {'support': 0.8345752608047691, 'agreement': 0.2173913043478261, 'direct_attack': 0.23728813559322032, 'undercutter_attack': 0.13953488372093023, 'partial': 0.2448979591836735}, 'support': {'support': 333, 'agreement': 68, 'direct_attack': 27, 'undercutter_attack': 35, 'partial': 37}, 'micro_avg': {'precision': 0.624, 'recall': 0.624, 'f1': 0.624, 'support': None}, 'macro_avg': {'precision': 0.4119127428763272, 'recall': 0.33329278858690625, 'f1': 0.33473750873008384, 'support': None}, 'weighted_avg': {'precision': 0.663897270657602, 'recall': 0.624, 'f1': 0.6260957912493714, 'support': None}}
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6737e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8306e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5317e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2077e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9201e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9915e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1986e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2613e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1542e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5062e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6377e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5337e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9530e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5235e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9613e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8825e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1247e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5979e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9068e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9443e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1009e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7064e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7411e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2593e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0908e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0402e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1372e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6070e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2906e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9230e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8405e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4167e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1982e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0058e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4377e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8251e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9161e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9210e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6584e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6251e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8281e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2287e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0309e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4145e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7804e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4442e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8695e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6528e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6255e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2327e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4374e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6880e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2879e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6034e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9220e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1679e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5208e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8652e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6615e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1281e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2912e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8656e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3681e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4586e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1266e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9097e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3993e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7424e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1281e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4692e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5131e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8924e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9345e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9837e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9513e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6802e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8171e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9382e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8675e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4317e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2951e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4677e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4620e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0502e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8081e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1773e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6464e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6073e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4175e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8323e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4517e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0211e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4666e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9824e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3155e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7523e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3994e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3094e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9240e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9010e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2956e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4828e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0675e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6295e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0191e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3288e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1304e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6372e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7069e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1395e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9999e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7000e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9462e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6243e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7942e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7644e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2965e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3249e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1965e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6658e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4136e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5498e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2103e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2895e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6715e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7526e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9183e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6831e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8808e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4678e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8021e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3187e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9637e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2784e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8588e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5943e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3600e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4842e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4355e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4828e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6667e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4131e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5819e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5386e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1995e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1437e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8029e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4339e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8710e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9627e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9379e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2996e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7592e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6554e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7335e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8855e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5983e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3937e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5489e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7709e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8053e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5952e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3751e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2155e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9685e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1061e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7865e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8746e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5910e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6154e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9798e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7324e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1240e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1500e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7523e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2976e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9353e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4880e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4459e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4731e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1484e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3431e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0791e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9824e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1883e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1725e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0616, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6197e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1571e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5772e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0060e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9726e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7512e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0436e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6212e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1375e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0226e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3276e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2610e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9897e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4465e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3842e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1701e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1723e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6050e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8556e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6536e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1523e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6469e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8031e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4275e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9197e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7232e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7123e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1580e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7084e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3998e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1995e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9016e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7242e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7347e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7142e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0300e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3708e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4041e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3314e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4850e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9604e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6013e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7341e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7974e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5733e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1330e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6164e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9530e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5667e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0058e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2004e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8907e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6295e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4435e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3072e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5822e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5780e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5628e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4769e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5174e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2298e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3112e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1281e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7952e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5319e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9573e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0835e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3206e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5797e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7562e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6645e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7069e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3284e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5014e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2943e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5304e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7545e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9673e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7605e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9414e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9856e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1801e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3163e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3633e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5878e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6204e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1692e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4741e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1519e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8799e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0980e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7696e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6223e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5274e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9934e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9257e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1005e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6251e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1005e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9059e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7147e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5760e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8021e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9794e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3496e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0715e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7971e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7605e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9261e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8202e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6606e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1286e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7030e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5145e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1501e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6567e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2917e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2704e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7595e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7432e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5032e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3708e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9271e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4135e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6043e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5650e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5011e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9544e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2891e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8401e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5183e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9783e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9923e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2882e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6584e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1049e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8589e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1693e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7999e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6384e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6588e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6656e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1635e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2432e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6199e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2810e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8223e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2004e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3185e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5931e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4770e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2800e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6334e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7917e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7947e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5646e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5040e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9270e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8688e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6030e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4253e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2722e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3224e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8728e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9030e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9050e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7618e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4850e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8678e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7861e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9119e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6619e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8786e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8068e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2398e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3329e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1580e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8847e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8262e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5588e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6076e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8246e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6152e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7255e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7305e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8894e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2113e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5637e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3033e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7133e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9888e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2561e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3783e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8604e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7739e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8469e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2786e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0027e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1856e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6305e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2004e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4902e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9685e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0920e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9067e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2458e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7960e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7038e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2911e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0766e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6638e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0973e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2026e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6980e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4321e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0369e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7644e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8868e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4470e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2349e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4962e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1300e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4071e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7575e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3366e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6637e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8141e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0472e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2224e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1731e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9533e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4289e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6615e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6416e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8522e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8648e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9634e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8069e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6378e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0634e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3812e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4561e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2392e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3542e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8970e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9314e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2670e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8387e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0551e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0187e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9120e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7091e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1514e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1783e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2194e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6558e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7354e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3702e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8849e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0996e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4369e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1925e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2821e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1654e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1333e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6744e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8319e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2916e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1414e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0785e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3950e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6312e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3547e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6433e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3155e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8646e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1193e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6251e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8822e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4011e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9618e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4927e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3093e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7792e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4344e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0862e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8341e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1186e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8422e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4861e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9361e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7129e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7468e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9257e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6433e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0112e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2479e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0067e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9257e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8604e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2670e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3714e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2458e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3479e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0938e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8954e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7768e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4836e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2929e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8232e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7649e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5598e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6626e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5222e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3841e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0879e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2280e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5888e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2155e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6433e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8232e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2825e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4120e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5892e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1874e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2043e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4459e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8401e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2576e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1381e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7005e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8786e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1580e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1871e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
	Train size: 50 Test size: 50


		-------------RUN 1-----------
			------------EPOCH 1---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.0, 'agreement': 0.0, 'direct_attack': 0.0, 'undercutter_attack': 0.0, 'partial': 0.06463414634146342}, 'recall': {'support': 0.0, 'agreement': 0.0, 'direct_attack': 0.0, 'undercutter_attack': 0.0, 'partial': 1.0}, 'f1': {'support': 0.0, 'agreement': 0.0, 'direct_attack': 0.0, 'undercutter_attack': 0.0, 'partial': 0.12142038946162657}, 'support': {'support': 945, 'agreement': 281, 'direct_attack': 141, 'undercutter_attack': 167, 'partial': 106}, 'micro_avg': {'precision': 0.06463414634146342, 'recall': 0.06463414634146342, 'f1': 0.06463414634146342, 'support': None}, 'macro_avg': {'precision': 0.012926829268292684, 'recall': 0.2, 'f1': 0.024284077892325315, 'support': None}, 'weighted_avg': {'precision': 0.004177572873289709, 'recall': 0.06463414634146342, 'f1': 0.007847903221300254, 'support': None}}
Loss: tensor(0.9114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0950, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0738, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5972, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8560, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5956, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6921, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6997, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6806, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6843, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3994, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9860, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6817, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3813, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3817, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3890, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6844, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6985, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3374, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6694, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6862, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2929, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6843, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6701, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6868, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7641, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6927, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6680, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4769, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5972, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6662, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0940, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5903, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1750, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5994, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4801, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4860, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8553, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4972, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0753, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0739, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4929, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0662, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1635, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5956, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5660, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5817, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8693, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9635, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4713, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1987, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0962, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4913, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6843, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9701, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0921, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9641, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6761, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0720, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2871, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2971, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4871, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4971, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3798, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8777, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2916, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 2---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6292446292446292, 'agreement': 0.609375, 'direct_attack': 0.22, 'undercutter_attack': 0.29411764705882354, 'partial': 0.5}, 'recall': {'support': 0.961864406779661, 'agreement': 0.2765957446808511, 'direct_attack': 0.07801418439716312, 'undercutter_attack': 0.029940119760479042, 'partial': 0.009433962264150943}, 'f1': {'support': 0.7607875994972769, 'agreement': 0.3804878048780488, 'direct_attack': 0.11518324607329844, 'undercutter_attack': 0.05434782608695651, 'partial': 0.018518518518518517}, 'support': {'support': 944, 'agreement': 282, 'direct_attack': 141, 'undercutter_attack': 167, 'partial': 106}, 'micro_avg': {'precision': 0.6115853658536585, 'recall': 0.6115853658536585, 'f1': 0.6115853658536585, 'support': None}, 'macro_avg': {'precision': 0.45054745526069057, 'recall': 0.27116968357646104, 'f1': 0.26586499901081984, 'support': None}, 'weighted_avg': {'precision': 0.5481636140644839, 'recall': 0.6115853658536585, 'f1': 0.5199761844614993, 'support': None}}
Loss: tensor(1.7480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0693, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1701, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2719, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8652, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6662, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9713, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8761, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5971, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7693, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9714, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6773, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7915, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3481, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9744, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1654, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6569, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2680, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4913, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0801, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2765, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2831, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1713, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0806, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3947, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2701, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4671, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0852, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6662, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5635, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1765, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4965, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8965, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0738, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1915, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1921, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2796, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2817, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1604, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2701, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1997, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9983, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9785, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5956, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3972, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0632, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6777, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8740, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9922, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1844, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4898, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9922, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6632, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2972, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4971, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7616, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2998, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2843, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4837, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8671, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7922, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3915, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1797, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2852, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1852, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 3---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7442660550458715, 'agreement': 0.38415841584158417, 'direct_attack': 0.12105263157894737, 'undercutter_attack': 0.19696969696969696, 'partial': 0.0}, 'recall': {'support': 0.6875, 'agreement': 0.6879432624113475, 'direct_attack': 0.16312056737588654, 'undercutter_attack': 0.07784431137724551, 'partial': 0.0}, 'f1': {'support': 0.7147577092511013, 'agreement': 0.4930114358322746, 'direct_attack': 0.13897280966767372, 'undercutter_attack': 0.11158798283261803, 'partial': 0.0}, 'support': {'support': 944, 'agreement': 282, 'direct_attack': 141, 'undercutter_attack': 167, 'partial': 106}, 'micro_avg': {'precision': 0.5359756097560976, 'recall': 0.5359756097560976, 'f1': 0.5359756097560976, 'support': None}, 'macro_avg': {'precision': 0.28928935988722, 'recall': 0.3232816282328959, 'f1': 0.2916659875167335, 'support': None}, 'weighted_avg': {'precision': 0.5249281644373174, 'recall': 0.5359756097560976, 'f1': 0.519506623008494, 'support': None}}
Loss: tensor(0.1077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5847, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1929, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3794, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3926, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0806, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0837, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8701, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2831, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0750, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1671, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2956, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3965, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1654, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0660, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0769, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0761, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0798, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8784, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0761, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4929, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8962, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7794, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7720, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3744, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8705, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0632, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0560, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6750, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0796, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0994, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1921, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5997, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7921, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2765, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1693, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6927, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0720, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6761, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0769, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2913, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6738, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0730, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2694, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8874, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5806, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1955, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3604, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0797, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5957, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5411, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 4---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7257590597453477, 'agreement': 0.44047619047619047, 'direct_attack': 0.23529411764705882, 'undercutter_attack': 0.13333333333333333, 'partial': 0.23684210526315788}, 'recall': {'support': 0.7841269841269841, 'agreement': 0.13167259786476868, 'direct_attack': 0.028368794326241134, 'undercutter_attack': 0.38323353293413176, 'partial': 0.08490566037735849}, 'f1': {'support': 0.7538148524923703, 'agreement': 0.20273972602739726, 'direct_attack': 0.05063291139240506, 'undercutter_attack': 0.19783616692426587, 'partial': 0.12499999999999997}, 'support': {'support': 945, 'agreement': 281, 'direct_attack': 141, 'undercutter_attack': 167, 'partial': 106}, 'micro_avg': {'precision': 0.5213414634146342, 'recall': 0.5213414634146342, 'f1': 0.5213414634146342, 'support': None}, 'macro_avg': {'precision': 0.3543409612930176, 'recall': 0.28246151392589686, 'f1': 0.2660047313672877, 'support': None}, 'weighted_avg': {'precision': 0.5427832447536339, 'recall': 0.5213414634146342, 'f1': 0.5016785237815061, 'support': None}}
Loss: tensor(0.0881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7796, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4744, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1994, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0753, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1922, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0616, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0374, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3774, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1796, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0794, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0705, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1962, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0962, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0837, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2705, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0632, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0785, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0601, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3913, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0997, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0719, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3935, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0569, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0719, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4871, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0694, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0785, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0826, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0987, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 5---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7625145518044237, 'agreement': 0.3170731707317073, 'direct_attack': 0.17142857142857143, 'undercutter_attack': 0.1488673139158576, 'partial': 0.23076923076923078}, 'recall': {'support': 0.6931216931216931, 'agreement': 0.04609929078014184, 'direct_attack': 0.0851063829787234, 'undercutter_attack': 0.5508982035928144, 'partial': 0.11428571428571428}, 'f1': {'support': 0.7261640798226163, 'agreement': 0.0804953560371517, 'direct_attack': 0.11374407582938388, 'undercutter_attack': 0.23439490445859873, 'partial': 0.15286624203821655}, 'support': {'support': 945, 'agreement': 282, 'direct_attack': 141, 'undercutter_attack': 167, 'partial': 105}, 'micro_avg': {'precision': 0.47804878048780486, 'recall': 0.47804878048780486, 'f1': 0.47804878048780486, 'support': None}, 'macro_avg': {'precision': 0.3261305677299582, 'recall': 0.29790225695181743, 'f1': 0.26153293163719343, 'support': None}, 'weighted_avg': {'precision': 0.5385694663583341, 'recall': 0.47804878048780486, 'f1': 0.4757058323081652, 'support': None}}
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5900, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0950, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0750, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2947, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0978, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0740, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0750, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1427, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1374, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0998, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6978, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0654, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0983, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0719, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6794, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1912, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0751, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1913, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9633, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 6---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7117202268431002, 'agreement': 0.5660377358490566, 'direct_attack': 0.15879828326180256, 'undercutter_attack': 0.1796116504854369, 'partial': 0.2}, 'recall': {'support': 0.7976694915254238, 'agreement': 0.10638297872340426, 'direct_attack': 0.2624113475177305, 'undercutter_attack': 0.2215568862275449, 'partial': 0.16981132075471697}, 'f1': {'support': 0.7522477522477524, 'agreement': 0.1791044776119403, 'direct_attack': 0.1978609625668449, 'undercutter_attack': 0.19839142091152814, 'partial': 0.18367346938775508}, 'support': {'support': 944, 'agreement': 282, 'direct_attack': 141, 'undercutter_attack': 167, 'partial': 106}, 'micro_avg': {'precision': 0.5335365853658537, 'recall': 0.5335365853658537, 'f1': 0.5335365853658537, 'support': None}, 'macro_avg': {'precision': 0.36323357928787925, 'recall': 0.31156640494976406, 'f1': 0.30225561654516414, 'support': None}, 'weighted_avg': {'precision': 0.5518733165977456, 'recall': 0.5335365853658537, 'f1': 0.5128832265717669, 'support': None}}
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0744, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1796, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 7---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7018900343642611, 'agreement': 0.4090909090909091, 'direct_attack': 0.18292682926829268, 'undercutter_attack': 0.11330049261083744, 'partial': 0.2153846153846154}, 'recall': {'support': 0.8645502645502645, 'agreement': 0.06382978723404255, 'direct_attack': 0.21428571428571427, 'undercutter_attack': 0.1377245508982036, 'partial': 0.1320754716981132}, 'f1': {'support': 0.7747747747747746, 'agreement': 0.11042944785276074, 'direct_attack': 0.19736842105263158, 'undercutter_attack': 0.12432432432432432, 'partial': 0.16374269005847955}, 'support': {'support': 945, 'agreement': 282, 'direct_attack': 140, 'undercutter_attack': 167, 'partial': 106}, 'micro_avg': {'precision': 0.55, 'recall': 0.55, 'f1': 0.55, 'support': None}, 'macro_avg': {'precision': 0.3245185761437831, 'recall': 0.2824931577332676, 'f1': 0.2741279316125942, 'support': None}, 'weighted_avg': {'precision': 0.5158606258732946, 'recall': 0.55, 'f1': 0.505520568727055, 'support': None}}
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0750, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0553, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3929, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0831, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 8---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7325456498388829, 'agreement': 0.49557522123893805, 'direct_attack': 0.14429530201342283, 'undercutter_attack': 0.16595744680851063, 'partial': 0.15873015873015872}, 'recall': {'support': 0.7216931216931217, 'agreement': 0.19858156028368795, 'direct_attack': 0.3049645390070922, 'undercutter_attack': 0.23353293413173654, 'partial': 0.09523809523809523}, 'f1': {'support': 0.7270788912579957, 'agreement': 0.28354430379746837, 'direct_attack': 0.19589977220956722, 'undercutter_attack': 0.19402985074626866, 'partial': 0.11904761904761904}, 'support': {'support': 945, 'agreement': 282, 'direct_attack': 141, 'undercutter_attack': 167, 'partial': 105}, 'micro_avg': {'precision': 0.5060975609756098, 'recall': 0.5060975609756098, 'f1': 0.5060975609756098, 'support': None}, 'macro_avg': {'precision': 0.3394207557259826, 'recall': 0.31080205007074674, 'f1': 0.3039200874117838, 'support': None}, 'weighted_avg': {'precision': 0.5467896642406741, 'recall': 0.5060975609756098, 'f1': 0.5119353041865048, 'support': None}}
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9921e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6197e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5683e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9365e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4159e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8195e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9947, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3403e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3403e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1041e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8680e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7469e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9204e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4885e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6500e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4674e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2171e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2907e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0948e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 9---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7228915662650602, 'agreement': 0.4827586206896552, 'direct_attack': 0.1444866920152091, 'undercutter_attack': 0.1572052401746725, 'partial': 0.13829787234042554}, 'recall': {'support': 0.7627118644067796, 'agreement': 0.09929078014184398, 'direct_attack': 0.2695035460992908, 'undercutter_attack': 0.2155688622754491, 'partial': 0.12264150943396226}, 'f1': {'support': 0.7422680412371134, 'agreement': 0.1647058823529412, 'direct_attack': 0.18811881188118815, 'undercutter_attack': 0.18181818181818182, 'partial': 0.13}, 'support': {'support': 944, 'agreement': 282, 'direct_attack': 141, 'undercutter_attack': 167, 'partial': 106}, 'micro_avg': {'precision': 0.5091463414634146, 'recall': 0.5091463414634146, 'f1': 0.5091463414634146, 'support': None}, 'macro_avg': {'precision': 0.32912799829700445, 'recall': 0.29394331247146516, 'f1': 0.28138218345788496, 'support': None}, 'weighted_avg': {'precision': 0.5364835626464021, 'recall': 0.5091463414634146, 'f1': 0.498668584506249, 'support': None}}
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6570e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7760e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2858e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2040e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2231e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0252e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9709e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6621e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5985e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5429e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3694, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5459e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3947e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1707e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6943e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3473e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5440e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7066e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0475e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 10---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7178502879078695, 'agreement': 0.5194805194805194, 'direct_attack': 0.1606425702811245, 'undercutter_attack': 0.16216216216216217, 'partial': 0.14942528735632185}, 'recall': {'support': 0.7923728813559322, 'agreement': 0.14184397163120568, 'direct_attack': 0.28368794326241137, 'undercutter_attack': 0.17964071856287425, 'partial': 0.12264150943396226}, 'f1': {'support': 0.7532729103726082, 'agreement': 0.22284122562674097, 'direct_attack': 0.20512820512820512, 'undercutter_attack': 0.17045454545454547, 'partial': 0.13471502590673576}, 'support': {'support': 944, 'agreement': 282, 'direct_attack': 141, 'undercutter_attack': 167, 'partial': 106}, 'micro_avg': {'precision': 0.5310975609756098, 'recall': 0.5310975609756098, 'f1': 0.5310975609756098, 'support': None}, 'macro_avg': {'precision': 0.3419121654375995, 'recall': 0.3040374048492772, 'f1': 0.2972823824977671, 'support': None}, 'weighted_avg': {'precision': 0.5425091111152591, 'recall': 0.5310975609756098, 'f1': 0.5156095315723068, 'support': None}}
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2403e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3452e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9436e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0415e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6954e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4886e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3976e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6458e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8064e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8861e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6631e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3128e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1363e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3008e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6793e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0455e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2948e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8892e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6491e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1454e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9405e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6933e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8014e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4290e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6530e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8791e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3130e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8195e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3775e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9244e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7155e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 11---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7189239332096475, 'agreement': 0.49, 'direct_attack': 0.17061611374407584, 'undercutter_attack': 0.1694915254237288, 'partial': 0.16216216216216217}, 'recall': {'support': 0.8201058201058201, 'agreement': 0.17375886524822695, 'direct_attack': 0.2553191489361702, 'undercutter_attack': 0.18072289156626506, 'partial': 0.11320754716981132}, 'f1': {'support': 0.7661888284725655, 'agreement': 0.25654450261780104, 'direct_attack': 0.20454545454545453, 'undercutter_attack': 0.1749271137026239, 'partial': 0.13333333333333336}, 'support': {'support': 945, 'agreement': 282, 'direct_attack': 141, 'undercutter_attack': 166, 'partial': 106}, 'micro_avg': {'precision': 0.55, 'recall': 0.55, 'f1': 0.55, 'support': None}, 'macro_avg': {'precision': 0.34223874690792283, 'recall': 0.30862285460525873, 'f1': 0.30710784653435563, 'support': None}, 'weighted_avg': {'precision': 0.540819982518634, 'recall': 0.55, 'f1': 0.5295159365510198, 'support': None}}
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0616, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2584e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8670e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6993e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4923e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5632e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8477e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4330e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3179e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1585e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3987e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9567e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7124e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4229e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1081e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1666e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6217e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5319e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7731e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8941e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4581e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2867e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0617e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9477e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4825e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9264e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6491e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5551e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7599e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2382e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7073e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2342e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2161e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5743e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4311e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0112e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7580e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4441e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1262e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9022e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0888e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0110e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6600e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5521e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6470e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5310e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6176e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0294e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8104e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5229e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1706e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1777e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7367e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4734e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2140e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3270e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0273e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6055e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0556e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3634e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8962e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 12---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.707774798927614, 'agreement': 0.5, 'direct_attack': 0.18716577540106952, 'undercutter_attack': 0.14942528735632185, 'partial': 0.15853658536585366}, 'recall': {'support': 0.8389830508474576, 'agreement': 0.13829787234042554, 'direct_attack': 0.24822695035460993, 'undercutter_attack': 0.15568862275449102, 'partial': 0.12264150943396226}, 'f1': {'support': 0.7678138633058652, 'agreement': 0.21666666666666667, 'direct_attack': 0.2134146341463415, 'undercutter_attack': 0.15249266862170088, 'partial': 0.13829787234042554}, 'support': {'support': 944, 'agreement': 282, 'direct_attack': 141, 'undercutter_attack': 167, 'partial': 106}, 'micro_avg': {'precision': 0.551829268292683, 'recall': 0.551829268292683, 'f1': 0.551829268292683, 'support': None}, 'macro_avg': {'precision': 0.34058048941017177, 'recall': 0.3007676011461893, 'f1': 0.29773714101619997, 'support': None}, 'weighted_avg': {'precision': 0.5349321253393321, 'recall': 0.551829268292683, 'f1': 0.5220326832337074, 'support': None}}
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3008e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3270e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7196e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4511e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6470e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8274e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3291e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3622e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8064e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3554e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9033e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3905e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6074e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1465e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9255e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6791e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5773e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6127e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2070e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2342e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9505e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0748e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0031e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7136e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9335e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2401e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1373e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3865e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8023e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0273e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6137e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0597e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5773, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8759e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3887e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5974e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7498e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1535e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9234e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3794e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2077e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4471e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3261e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5156e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8457e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6379e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1523e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1172e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5692e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9183e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3584e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5783e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7195e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6246e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8183e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6973e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1000e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5217e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4309e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1666e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3824e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4947e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1533e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6791e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8989e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9646e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2110e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4704e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1120e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5824e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3684e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3796e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3582e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6591e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 13---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7199621570482497, 'agreement': 0.5, 'direct_attack': 0.16216216216216217, 'undercutter_attack': 0.1595744680851064, 'partial': 0.16049382716049382}, 'recall': {'support': 0.8052910052910053, 'agreement': 0.16370106761565836, 'direct_attack': 0.2553191489361702, 'undercutter_attack': 0.17964071856287425, 'partial': 0.12264150943396226}, 'f1': {'support': 0.7602397602397601, 'agreement': 0.24664879356568364, 'direct_attack': 0.19834710743801653, 'undercutter_attack': 0.16901408450704225, 'partial': 0.1390374331550802}, 'support': {'support': 945, 'agreement': 281, 'direct_attack': 141, 'undercutter_attack': 167, 'partial': 106}, 'micro_avg': {'precision': 0.5402439024390244, 'recall': 0.5402439024390244, 'f1': 0.5402439024390244, 'support': None}, 'macro_avg': {'precision': 0.34043852289120247, 'recall': 0.3053186899679341, 'f1': 0.30265743578111654, 'support': None}, 'weighted_avg': {'precision': 0.5410916982467598, 'recall': 0.5402439024390244, 'f1': 0.5235763088990277, 'support': None}}
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9567e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7247e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9637e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1535e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1514e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6498e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1756e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7671e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8405e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1917e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7074e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7559e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8619e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5105e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6186e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9213e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7024e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0908e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9567e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7911e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0627e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8992e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2544e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3523e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4390e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1131e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6801e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3048e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4935e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9195e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2564e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7327e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3582e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2776e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7557e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0323e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0797e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9415e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5197e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8042e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0646e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5247e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4077e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1554e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3512e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4127e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2180e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2068e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2786e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8668e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7142e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2977e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3624e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8133e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1595e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4450e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7327e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5429e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9265e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3715e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7830e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1968e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4956e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7678e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6913e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9779e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7799e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7327e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4330e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9335e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0494e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9244e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0040e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4208e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6034e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4932e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5298e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7842e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2422e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9394e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4481e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1968e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5317e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2411e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9648e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7671e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3472e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0294e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0857e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5813e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4329e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6279e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 14---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7140238313473877, 'agreement': 0.5205479452054794, 'direct_attack': 0.16203703703703703, 'undercutter_attack': 0.15555555555555556, 'partial': 0.1625}, 'recall': {'support': 0.8252118644067796, 'agreement': 0.1347517730496454, 'direct_attack': 0.24822695035460993, 'undercutter_attack': 0.16766467065868262, 'partial': 0.12264150943396226}, 'f1': {'support': 0.7656019656019656, 'agreement': 0.2140845070422535, 'direct_attack': 0.19607843137254902, 'undercutter_attack': 0.16138328530259366, 'partial': 0.13978494623655913}, 'support': {'support': 944, 'agreement': 282, 'direct_attack': 141, 'undercutter_attack': 167, 'partial': 106}, 'micro_avg': {'precision': 0.5445121951219513, 'recall': 0.5445121951219513, 'f1': 0.5445121951219513, 'support': None}, 'macro_avg': {'precision': 0.342932873829092, 'recall': 0.29969935358073596, 'f1': 0.2953866271111842, 'support': None}, 'weighted_avg': {'precision': 0.5407823276462678, 'recall': 0.5445121951219513, 'f1': 0.5198264379782371, 'support': None}}
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0788e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2855e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0434e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1181e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4511e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5147e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1403e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2797e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5753e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9375e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0212e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0463e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9919e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3997e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1716e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5166e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4855e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9395e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3047e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9667e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8771e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3724e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2886e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2352e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1995e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9649e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4450e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4319e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5519e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8638e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8032e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8800e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3107e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5471e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3360e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0869e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5440e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1009e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2362e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4923e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4593e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7166e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3279e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0324e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0536e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8314e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7368e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5037e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4127e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0617e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0939e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9679e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0476e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2180e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9637e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5915e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8155e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8052e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1423e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3452e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0938e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9555e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8870e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6650e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0848e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4472e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8882e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9858e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4611e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1887e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8559e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4966e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7034e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9184e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8014e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2371e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7769e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2290e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9173e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0769e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2238e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9152e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7418e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3624e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9516e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5490e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3542e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6449e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4320e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 15---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7190243902439024, 'agreement': 0.49411764705882355, 'direct_attack': 0.1590909090909091, 'undercutter_attack': 0.15846994535519127, 'partial': 0.1927710843373494}, 'recall': {'support': 0.7807203389830508, 'agreement': 0.14893617021276595, 'direct_attack': 0.2978723404255319, 'undercutter_attack': 0.17365269461077845, 'partial': 0.1509433962264151}, 'f1': {'support': 0.7486033519553073, 'agreement': 0.22888283378746593, 'direct_attack': 0.2074074074074074, 'undercutter_attack': 0.16571428571428573, 'partial': 0.1693121693121693}, 'support': {'support': 944, 'agreement': 282, 'direct_attack': 141, 'undercutter_attack': 167, 'partial': 106}, 'micro_avg': {'precision': 0.5280487804878049, 'recall': 0.5280487804878049, 'f1': 0.5280487804878049, 'support': None}, 'macro_avg': {'precision': 0.3446947952172351, 'recall': 0.31042498809170843, 'f1': 0.3039840096353271, 'support': None}, 'weighted_avg': {'precision': 0.5411159968638575, 'recall': 0.5280487804878049, 'f1': 0.5159099655363997, 'support': None}}
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8880e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6670e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5045e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1222e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2501e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5156e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4279e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4977e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4651e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8921e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6710e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8214e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9154e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3502e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7457e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7509e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4833e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4923e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0687e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4793e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5340e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1737e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7902e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3906e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2907e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2766e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5258e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4239e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8759e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2189e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5851e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4532e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4803e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4239e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9301e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2946e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8205e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6115e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4916e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5840e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9748e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6379e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7387e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3261e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8083e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1968e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0361e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5370e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8216e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7690e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0959e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4681e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9678e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3098e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4339e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0645e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5105e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1756e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2737e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0494e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8647e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1484e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2281e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3249e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9022e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0787e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0324e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5973e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1737e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0222e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2292e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9404e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2159e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1917e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0233e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5438e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6489e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8245e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9253e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9322e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4037e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1039e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9113e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4329e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7730e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1351e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4381e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3493e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7103e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4499e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2722e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3531e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7042e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8305e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8314e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6710e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6286e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8393e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9174e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0585e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6793e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8223e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3673e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4478e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0353e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0633e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0243e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2298e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5842e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3237e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8417e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5922e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5873e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8922, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 16---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7066189624329159, 'agreement': 0.5111111111111111, 'direct_attack': 0.1837837837837838, 'undercutter_attack': 0.15060240963855423, 'partial': 0.16049382716049382}, 'recall': {'support': 0.8359788359788359, 'agreement': 0.16370106761565836, 'direct_attack': 0.24113475177304963, 'undercutter_attack': 0.1497005988023952, 'partial': 0.12264150943396226}, 'f1': {'support': 0.7658749394086283, 'agreement': 0.24797843665768193, 'direct_attack': 0.2085889570552147, 'undercutter_attack': 0.15015015015015015, 'partial': 0.1390374331550802}, 'support': {'support': 945, 'agreement': 281, 'direct_attack': 141, 'undercutter_attack': 167, 'partial': 106}, 'micro_avg': {'precision': 0.5536585365853659, 'recall': 0.5536585365853659, 'f1': 0.5536585365853659, 'support': None}, 'macro_avg': {'precision': 0.34252201882537175, 'recall': 0.3026313527207803, 'f1': 0.302325983285351, 'support': None}, 'weighted_avg': {'precision': 0.5362521971484708, 'recall': 0.5536585365853659, 'f1': 0.5260108807172325, 'support': None}}
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6709e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8710e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8761e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5287e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6095e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2170e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3512e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0334e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4672e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2450e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2228e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2482e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7550e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1323e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2706e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6558e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4398e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8738e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0412e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0264e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4583e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7427e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6649e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0375e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2019e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2865e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9991e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1351e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0264e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2301e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0291e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9616e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5925e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7872e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8142e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6852e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6407e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7809e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1644e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3826e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5157e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7517e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1524e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2150e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2059e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6400e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6640e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5871e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8356e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3500e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0633e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1208e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1938e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8771e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7579e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7497e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2229e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9586e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9262e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8619e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5096e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9906e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3997e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3963e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7640e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8898e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9335e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0415e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9667e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1919e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6952e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8277e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5680e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0784e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7063e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6851e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8517e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4532e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2068e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5582e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6782e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7769e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6278e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2281e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8295e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5931e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9758e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1535e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3210e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2147e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3330e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6490e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3963e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8941e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1928e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6791e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6803e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9477e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7780e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9776e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8800e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5652e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8911e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4591e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5671e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8739e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0615e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0748e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1935e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7517e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4541e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7003e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0663e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4905e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8831e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5661e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9132e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7778e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6165e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8284e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7578e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1020e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8486e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2885e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6688e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8425e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4772e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3055e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1169e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2139e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5853e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6893e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6035e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3803e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7547e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1443e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5862e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8968e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9837e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3965e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 17---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7070347284060552, 'agreement': 0.5111111111111111, 'direct_attack': 0.19101123595505617, 'undercutter_attack': 0.16071428571428573, 'partial': 0.16049382716049382}, 'recall': {'support': 0.8411016949152542, 'agreement': 0.16312056737588654, 'direct_attack': 0.24113475177304963, 'undercutter_attack': 0.16167664670658682, 'partial': 0.12264150943396226}, 'f1': {'support': 0.768263183357523, 'agreement': 0.24731182795698925, 'direct_attack': 0.21316614420062696, 'undercutter_attack': 0.16119402985074627, 'partial': 0.1390374331550802}, 'support': {'support': 944, 'agreement': 282, 'direct_attack': 141, 'undercutter_attack': 167, 'partial': 106}, 'micro_avg': {'precision': 0.5573170731707318, 'recall': 0.5573170731707318, 'f1': 0.5573170731707318, 'support': None}, 'macro_avg': {'precision': 0.34607303766940045, 'recall': 0.3059350340409479, 'f1': 0.3057945237041931, 'support': None}, 'weighted_avg': {'precision': 0.5380233735436649, 'recall': 0.5573170731707318, 'f1': 0.5284732791494965, 'support': None}}
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5632e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0209e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7930e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2735e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0140e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3473e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6902e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2976e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7347e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9253e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9101e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5650e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5983e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5953e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6891e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6297e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2401e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4932e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1057e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2976e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7124e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1594e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2622e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7860e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9406e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4450e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4601e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5007e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2240e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1208e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3548e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1312e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6476e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2068e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9677e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7861e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7194e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3543e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3291e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0243e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9021e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5873e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0444e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9769e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1877e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5023e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4995e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7993e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4520e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6539e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3724e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1584e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0596e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3149e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3237e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7811e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9001e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8426e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6015e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4380e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3573e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1535e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2311e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6045e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0545e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9737e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5105e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0372e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5218e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1029e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0918e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8668e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1511e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3531e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6537e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9274e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4602e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9698e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0815e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4703e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4783e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4419e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7757e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0555e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8950e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4872e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1926e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3954e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6334e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4236e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6985e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4995e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9604e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2070e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2624e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5460e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4106e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5511e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6367e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0455e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8738e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3058e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9040e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6619e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6793e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1069e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2510e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8367e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2873e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8838e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5014e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0070e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2934e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5400e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1372e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7478e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2259e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1835e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6588e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1353e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2670e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3742e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9180e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2170e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9699e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5247e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6549e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4893e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2583e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5650e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0676e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5056e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5801e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4500e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7922e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7135e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6187e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1775e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6860e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1000e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1081e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8626e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1360e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 18---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7065602836879432, 'agreement': 0.5068493150684932, 'direct_attack': 0.18181818181818182, 'undercutter_attack': 0.15294117647058825, 'partial': 0.15853658536585366}, 'recall': {'support': 0.8442796610169492, 'agreement': 0.13120567375886524, 'direct_attack': 0.24113475177304963, 'undercutter_attack': 0.15568862275449102, 'partial': 0.12264150943396226}, 'f1': {'support': 0.7693050193050194, 'agreement': 0.20845070422535208, 'direct_attack': 0.20731707317073172, 'undercutter_attack': 0.1543026706231454, 'partial': 0.13829787234042554}, 'support': {'support': 944, 'agreement': 282, 'direct_attack': 141, 'undercutter_attack': 167, 'partial': 106}, 'micro_avg': {'precision': 0.5530487804878049, 'recall': 0.5530487804878049, 'f1': 0.5530487804878049, 'support': None}, 'macro_avg': {'precision': 0.34134110848221205, 'recall': 0.29899004374746346, 'f1': 0.2955346679329348, 'support': None}, 'weighted_avg': {'precision': 0.5353090443941864, 'recall': 0.5530487804878049, 'f1': 0.5211383320699459, 'support': None}}
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3865e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8496e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2097e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3070e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1423e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2534e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3793e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6515e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6559e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3500e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1393e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7335e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7155e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8244e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7536e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5084e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1776e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8758e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8453e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0939e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5035e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5004e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4660e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8254e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5702e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8659e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9513e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0636e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6870e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1432e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2843e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3473e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5862e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2713e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9889e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6225e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0451e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0212e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2783e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4752e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4833e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2380e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9638e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1905e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1947e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6437e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2207e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9474e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1493e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7568e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6658e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3470e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3067e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9937e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0442e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8241e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7172e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8831e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6377e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9616e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0512e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9482e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2653e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7930e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3691e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8084e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8808e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0423e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4450e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3500e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1332e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8538e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1048e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9385e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8184e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0352e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9272e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7566e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9353e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6954e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9625e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2927e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1905e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0797e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5459e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3388e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9534e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0140e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7393e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5256e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1604e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8961e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1574e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4411e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7447e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2804e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1644e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3603e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3894e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9240e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6712e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9664e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4450e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6246e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7951e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2421e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1753e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9625e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9776e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9908e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3349e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3824e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7973e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9222e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1646e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7465e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6839e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2873e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0152e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1505e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4630e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9120e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8072e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9686e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8456e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0019e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8568e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1463e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4357e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9779e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7960e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9514e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8738e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3661e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3924e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8559e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7215e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9779e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6579e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1493e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4046e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1916e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1947e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9274e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4045e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3905e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0785, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4169e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4578e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6761e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9149e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4863e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8447e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7445e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1099e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3215e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3881e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4206e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3712e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4742e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7878e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9201e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3760e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6054e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7580e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1846e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1483e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6397e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2504e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6067e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0845e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3179e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 19---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7067137809187279, 'agreement': 0.475, 'direct_attack': 0.1907514450867052, 'undercutter_attack': 0.15204678362573099, 'partial': 0.15476190476190477}, 'recall': {'support': 0.847457627118644, 'agreement': 0.1347517730496454, 'direct_attack': 0.23404255319148937, 'undercutter_attack': 0.15568862275449102, 'partial': 0.12264150943396226}, 'f1': {'support': 0.770712909441233, 'agreement': 0.20994475138121546, 'direct_attack': 0.21019108280254778, 'undercutter_attack': 0.15384615384615385, 'partial': 0.1368421052631579}, 'support': {'support': 944, 'agreement': 282, 'direct_attack': 141, 'undercutter_attack': 167, 'partial': 106}, 'micro_avg': {'precision': 0.5548780487804879, 'recall': 0.5548780487804879, 'f1': 0.5548780487804879, 'support': None}, 'macro_avg': {'precision': 0.3358547828786137, 'recall': 0.29891641710964645, 'f1': 0.29630740054686167, 'support': None}, 'weighted_avg': {'precision': 0.5303538644602217, 'recall': 0.5548780487804879, 'f1': 0.5223121462971881, 'support': None}}
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4680e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1808e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0224e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2310e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5196e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0935, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2776e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4621e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0512e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9534e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9940e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6337e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8907e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0626e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4266e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9119e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8405e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1826e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7518e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4713e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8768e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5568e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0740, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9707e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3288e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7475e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7154e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0496e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8332e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8165e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1792e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6428e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3190e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9948e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6064e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7738e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8202e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9997e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0233e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9625e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6909e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2482e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8505e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5053e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5824e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0775e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8211e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8241e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8587e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1323e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9364e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4790e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2592e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9677e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0905e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7436e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0685e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7718e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1645e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1121e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0645e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8668e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4792e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3936e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8877e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7636e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3561e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9090e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3812e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6460e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7406e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9525e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3261e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6779e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6781e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3482e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7769e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0161e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9616e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6074e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8596e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2380e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0382e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8335e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1846e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5891e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0394e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5062e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9392e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8447e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0211e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9876e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4266e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5075e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0152e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1472e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1100e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4765e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3329e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8962e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2451e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7942e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2367e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8771e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8205e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6339e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9900e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9604e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6234e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2522e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1481e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2843e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9703e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4278e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5032e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7730e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4884e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8093e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5804e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6924e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7687e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0088e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8708e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7787e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7497e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4690e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0957e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3815e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7639e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9274e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2964e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5741e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2419e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9673e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7609e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5386e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2501e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8414e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0261e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7224e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9979e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8232e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8447e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6772e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3199e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3167e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1676e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4015e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9404e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5205e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9694e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0523e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9928e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1442e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9911e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8574e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6316e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2714e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2895e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2117e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2380e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6839e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5095e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9131e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6740e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6982e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7821e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3418e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3360e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7064e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1714e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8980e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2222e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8335e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9990e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6507e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9373e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9422e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2332e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9686e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4880e-05, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 20---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7140221402214022, 'agreement': 0.5, 'direct_attack': 0.16037735849056603, 'undercutter_attack': 0.17045454545454544, 'partial': 0.19047619047619047}, 'recall': {'support': 0.819047619047619, 'agreement': 0.14893617021276595, 'direct_attack': 0.24113475177304963, 'undercutter_attack': 0.18072289156626506, 'partial': 0.1509433962264151}, 'f1': {'support': 0.7629374075899458, 'agreement': 0.22950819672131148, 'direct_attack': 0.19263456090651557, 'undercutter_attack': 0.17543859649122806, 'partial': 0.16842105263157897}, 'support': {'support': 945, 'agreement': 282, 'direct_attack': 141, 'undercutter_attack': 166, 'partial': 106}, 'micro_avg': {'precision': 0.5463414634146342, 'recall': 0.5463414634146342, 'f1': 0.5463414634146342, 'support': None}, 'macro_avg': {'precision': 0.3470660469285408, 'recall': 0.30815696576522295, 'f1': 0.30578796286811605, 'support': None}, 'weighted_avg': {'precision': 0.5407622321904425, 'recall': 0.5463414634146342, 'f1': 0.5242890691050113, 'support': None}}
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2601e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4145e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0321e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3409e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8144e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7005e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6437e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2925e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8870e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2086e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9406e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5540e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0897e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4296e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6104e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9279e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4327e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3806e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3957e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4460e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8123e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1411e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6870e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2480e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2237e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2171e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8020e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0273e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3421e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9322e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5156e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5297e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6476e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8665e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6043e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5023e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6255e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7718e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3481e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0010e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5758e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0140e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4768e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0736e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9352e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5086e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0793e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0694e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5637e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6822e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4278e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3561e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3432e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5105e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1856e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7515e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8698e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1372e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8444e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2298e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7255e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0100e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1390e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4865e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0905e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2946e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7124e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9608e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3684e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1796e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3851e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3003e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2462e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7717e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0654e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6961e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3794e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3218e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1835e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1835e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9928e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0049e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9070e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5207e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4015e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1009e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2207e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1441e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7055e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0382e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4145e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8366e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2492e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0918e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1368e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2601e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8041e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7911e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4911e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2876e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6921e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2625e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1329e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4833e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8583e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5763e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5962e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9513e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7557e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2016e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8263e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1565e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2238e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5226e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3402e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9625e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8081e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8920e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0888e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5541e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2207e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5337e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9838e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0100e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2298e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6670e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4701e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1665e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0355e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1411e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8305e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5500e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4077e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0884e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8617e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7617e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7617e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5698e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5537e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6900e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2250e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8002e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0294e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7659e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1262e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9595e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6216e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4902e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4015e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8808e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4318e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6358e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5235e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2332e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3542e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4641e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4790e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9945e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5598e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2834e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9110e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4335e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6606e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3479e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2159e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3025e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9625e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6476e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1413e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3863e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3600e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0270e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3548e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0412e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2822e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5862e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2138e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3479e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)


		-------------RUN 2-----------
			------------EPOCH 1---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.0, 'agreement': 0.0, 'direct_attack': 0.0, 'undercutter_attack': 0.0, 'partial': 0.04388888888888889}, 'recall': {'support': 0.0, 'agreement': 0.0, 'direct_attack': 0.0, 'undercutter_attack': 0.0, 'partial': 1.0}, 'f1': {'support': 0.0, 'agreement': 0.0, 'direct_attack': 0.0, 'undercutter_attack': 0.0, 'partial': 0.08408728046833422}, 'support': {'support': 1108, 'agreement': 281, 'direct_attack': 163, 'undercutter_attack': 171, 'partial': 79}, 'micro_avg': {'precision': 0.04384017758046615, 'recall': 0.04384017758046615, 'f1': 0.04384017758046615, 'support': None}, 'macro_avg': {'precision': 0.008777777777777777, 'recall': 0.2, 'f1': 0.016817456093666843, 'support': None}, 'weighted_avg': {'precision': 0.0019240966826982364, 'recall': 0.04384017758046615, 'f1': 0.0036864013079902346, 'support': None}}
Loss: tensor(4.6048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7997, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6926, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5926, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8671, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8511, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8898, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2868, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7660, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3730, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8796, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7997, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3904, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7753, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3694, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4680, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8616, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6744, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2868, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5977, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5871, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5962, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7740, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1785, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0713, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8777, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4730, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2880, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3757, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0683, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6635, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7719, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8773, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7784, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2955, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7852, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5906, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6957, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1777, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9553, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3844, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6898, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1915, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2929, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0331, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 2---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7041984732824428, 'agreement': 0.37555555555555553, 'direct_attack': 0.0, 'undercutter_attack': 0.05521472392638037, 'partial': 0.04964539007092199}, 'recall': {'support': 0.6660649819494585, 'agreement': 0.6014234875444839, 'direct_attack': 0.0, 'undercutter_attack': 0.05263157894736842, 'partial': 0.08860759493670886}, 'f1': {'support': 0.6846011131725418, 'agreement': 0.4623803009575923, 'direct_attack': 0.0, 'undercutter_attack': 0.05389221556886228, 'partial': 0.06363636363636364}, 'support': {'support': 1108, 'agreement': 281, 'direct_attack': 163, 'undercutter_attack': 171, 'partial': 79}, 'micro_avg': {'precision': 0.5122086570477248, 'recall': 0.5122086570477248, 'f1': 0.5122086570477248, 'support': None}, 'macro_avg': {'precision': 0.2369228285670601, 'recall': 0.281745528675604, 'f1': 0.252901998667072, 'support': None}, 'weighted_avg': {'precision': 0.4989715444589743, 'recall': 0.5122086570477248, 'f1': 0.5009488010842441, 'support': None}}
Loss: tensor(0.8938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3784, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6971, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8701, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1738, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2927, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1785, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6616, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9927, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5601, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4900, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9898, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9757, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7874, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7978, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5713, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5683, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4777, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6844, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3714, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6765, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7751, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2761, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6971, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6374, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9806, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5950, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3898, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7962, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6843, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5935, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6921, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7652, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5880, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6773, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3860, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9511, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0983, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3950, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4868, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3714, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0985, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3761, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9844, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2874, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7604, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5806, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4927, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1813, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1652, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3694, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7843, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5985, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4635, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2553, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1529, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 3---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.79491833030853, 'agreement': 0.43373493975903615, 'direct_attack': 0.12300683371298406, 'undercutter_attack': 0.14411764705882352, 'partial': 0.02857142857142857}, 'recall': {'support': 0.3953068592057762, 'agreement': 0.5124555160142349, 'direct_attack': 0.3312883435582822, 'undercutter_attack': 0.28654970760233917, 'partial': 0.05063291139240506}, 'f1': {'support': 0.5280289330922243, 'agreement': 0.4698205546492659, 'direct_attack': 0.17940199335548174, 'undercutter_attack': 0.1917808219178082, 'partial': 0.0365296803652968}, 'support': {'support': 1108, 'agreement': 281, 'direct_attack': 163, 'undercutter_attack': 171, 'partial': 79}, 'micro_avg': {'precision': 0.38235294117647056, 'recall': 0.38235294117647056, 'f1': 0.3823529411764706, 'support': None}, 'macro_avg': {'precision': 0.30486983588216043, 'recall': 0.31524666755460745, 'f1': 0.2811123966760154, 'support': None}, 'weighted_avg': {'precision': 0.5824641523049714, 'recall': 0.38235294117647056, 'f1': 0.43396144502573547, 'support': None}}
Loss: tensor(0.4942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2847, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2852, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6874, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9680, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0998, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2927, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1940, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0860, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6694, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4604, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4873, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0680, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3904, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3890, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2601, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7796, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2616, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3739, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0957, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2798, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6693, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3791, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1632, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2997, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0977, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2481, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9912, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1784, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3560, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2873, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1641, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7922, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3693, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8956, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0739, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1783, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3983, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5935, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4971, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8757, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2903, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5922, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7754, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1874, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1798, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0785, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0852, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9652, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3940, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 4---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7568134171907757, 'agreement': 0.5018867924528302, 'direct_attack': 0.15363881401617252, 'undercutter_attack': 0.13245033112582782, 'partial': 0.11475409836065574}, 'recall': {'support': 0.6516245487364621, 'agreement': 0.47330960854092524, 'direct_attack': 0.3496932515337423, 'undercutter_attack': 0.11695906432748537, 'partial': 0.08860759493670886}, 'f1': {'support': 0.7002909796314258, 'agreement': 0.4871794871794871, 'direct_attack': 0.21348314606741575, 'undercutter_attack': 0.12422360248447206, 'partial': 0.10000000000000002}, 'support': {'support': 1108, 'agreement': 281, 'direct_attack': 163, 'undercutter_attack': 171, 'partial': 79}, 'micro_avg': {'precision': 0.521087680355161, 'recall': 0.521087680355161, 'f1': 0.521087680355161, 'support': None}, 'macro_avg': {'precision': 0.3319086906292524, 'recall': 0.3360388136150648, 'f1': 0.32503544307256016, 'support': None}, 'weighted_avg': {'precision': 0.5751038634873858, 'recall': 0.521087680355161, 'f1': 0.5420420811114812, 'support': None}}
Loss: tensor(0.6417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0998, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0553, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2739, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1983, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0604, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3773, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2738, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0374, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2740, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0844, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0922, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0740, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2947, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5950, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0569, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0694, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0481, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2427, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2714, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0837, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0511, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6885, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0921, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7374, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7777, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7868, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6797, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0481, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0955, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1662, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0950, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3831, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4798, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1977, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1714, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6940, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8852, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1903, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2769, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0824, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 5---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7343895619757689, 'agreement': 0.4189189189189189, 'direct_attack': 0.1782178217821782, 'undercutter_attack': 0.10757946210268948, 'partial': 0.08275862068965517}, 'recall': {'support': 0.7111913357400722, 'agreement': 0.1103202846975089, 'direct_attack': 0.11042944785276074, 'undercutter_attack': 0.2573099415204678, 'partial': 0.1518987341772152}, 'f1': {'support': 0.7226043099495645, 'agreement': 0.17464788732394365, 'direct_attack': 0.13636363636363635, 'undercutter_attack': 0.15172413793103448, 'partial': 0.10714285714285714}, 'support': {'support': 1108, 'agreement': 281, 'direct_attack': 163, 'undercutter_attack': 171, 'partial': 79}, 'micro_avg': {'precision': 0.4955604883462819, 'recall': 0.4955604883462819, 'f1': 0.4955604883462819, 'support': None}, 'macro_avg': {'precision': 0.30437287709384214, 'recall': 0.2682299487976049, 'f1': 0.25849656574220725, 'support': None}, 'weighted_avg': {'precision': 0.5468387208046093, 'recall': 0.4955604883462819, 'f1': 0.5029733728023923, 'support': None}}
Loss: tensor(0.0502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1927, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0754, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0903, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0635, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2714, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0427, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0791, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0662, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0998, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0985, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6972, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0773, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0604, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4843, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3890, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0777, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3903, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1977, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0785, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0860, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3155, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 6---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7881578947368421, 'agreement': 0.4497991967871486, 'direct_attack': 0.18796992481203006, 'undercutter_attack': 0.13673469387755102, 'partial': 0.058823529411764705}, 'recall': {'support': 0.5406137184115524, 'agreement': 0.398576512455516, 'direct_attack': 0.15337423312883436, 'undercutter_attack': 0.391812865497076, 'partial': 0.12658227848101267}, 'f1': {'support': 0.6413276231263384, 'agreement': 0.4226415094339623, 'direct_attack': 0.16891891891891891, 'undercutter_attack': 0.20272314674735248, 'partial': 0.08032128514056225}, 'support': {'support': 1108, 'agreement': 281, 'direct_attack': 163, 'undercutter_attack': 171, 'partial': 79}, 'micro_avg': {'precision': 0.451165371809101, 'recall': 0.451165371809101, 'f1': 0.451165371809101, 'support': None}, 'macro_avg': {'precision': 0.3242970479250673, 'recall': 0.32219192159479826, 'f1': 0.30318649667342684, 'support': None}, 'weighted_avg': {'precision': 0.5873142679725645, 'recall': 0.451165371809101, 'f1': 0.4982786315086635, 'support': None}}
Loss: tensor(0.0824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 7---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7479608482871125, 'agreement': 0.49162011173184356, 'direct_attack': 0.21929824561403508, 'undercutter_attack': 0.17857142857142858, 'partial': 0.10344827586206896}, 'recall': {'support': 0.8276173285198556, 'agreement': 0.31316725978647686, 'direct_attack': 0.3067484662576687, 'undercutter_attack': 0.14619883040935672, 'partial': 0.0379746835443038}, 'f1': {'support': 0.7857754927163668, 'agreement': 0.38260869565217387, 'direct_attack': 0.25575447570332477, 'undercutter_attack': 0.1607717041800643, 'partial': 0.05555555555555556}, 'support': {'support': 1108, 'agreement': 281, 'direct_attack': 163, 'undercutter_attack': 171, 'partial': 79}, 'micro_avg': {'precision': 0.6009988901220865, 'recall': 0.6009988901220865, 'f1': 0.6009988901220865, 'support': None}, 'macro_avg': {'precision': 0.34817978201329775, 'recall': 0.32634131370353237, 'f1': 0.32809318476149707, 'support': None}, 'weighted_avg': {'precision': 0.5778799186529824, 'recall': 0.6009988901220865, 'f1': 0.583641020672207, 'support': None}}
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8277e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 8---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7799564270152506, 'agreement': 0.376, 'direct_attack': 0.20108695652173914, 'undercutter_attack': 0.16201117318435754, 'partial': 0.07534246575342465}, 'recall': {'support': 0.6462093862815884, 'agreement': 0.501779359430605, 'direct_attack': 0.22699386503067484, 'undercutter_attack': 0.1695906432748538, 'partial': 0.13924050632911392}, 'f1': {'support': 0.7068114511352419, 'agreement': 0.4298780487804878, 'direct_attack': 0.2132564841498559, 'undercutter_attack': 0.1657142857142857, 'partial': 0.09777777777777777}, 'support': {'support': 1108, 'agreement': 281, 'direct_attack': 163, 'undercutter_attack': 171, 'partial': 79}, 'micro_avg': {'precision': 0.5183129855715871, 'recall': 0.5183129855715871, 'f1': 0.5183129855715871, 'support': None}, 'macro_avg': {'precision': 0.31887940449495444, 'recall': 0.33676275206936723, 'f1': 0.3226876095115298, 'support': None}, 'weighted_avg': {'precision': 0.5750726195643656, 'recall': 0.5183129855715871, 'f1': 0.5409351907786787, 'support': None}}
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0904, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0827e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 9---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7481044650379107, 'agreement': 0.5038167938931297, 'direct_attack': 0.21476510067114093, 'undercutter_attack': 0.13063063063063063, 'partial': 0.11504424778761062}, 'recall': {'support': 0.8014440433212996, 'agreement': 0.23487544483985764, 'direct_attack': 0.19631901840490798, 'undercutter_attack': 0.1695906432748538, 'partial': 0.16455696202531644}, 'f1': {'support': 0.7738562091503267, 'agreement': 0.3203883495145631, 'direct_attack': 0.20512820512820512, 'undercutter_attack': 0.1475826972010178, 'partial': 0.13541666666666666}, 'support': {'support': 1108, 'agreement': 281, 'direct_attack': 163, 'undercutter_attack': 171, 'partial': 79}, 'micro_avg': {'precision': 0.5704772475027747, 'recall': 0.5704772475027747, 'f1': 0.5704772475027747, 'support': None}, 'macro_avg': {'precision': 0.3424722476040845, 'recall': 0.3133572223732471, 'f1': 0.3164744255321559, 'support': None}, 'weighted_avg': {'precision': 0.5754191515918033, 'recall': 0.5704772475027747, 'f1': 0.5642798342264663, 'support': None}}
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5561e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0948e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0604, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3018e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6847, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0635, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0753, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 10---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7446457990115322, 'agreement': 0.515625, 'direct_attack': 0.21359223300970873, 'undercutter_attack': 0.15384615384615385, 'partial': 0.09090909090909091}, 'recall': {'support': 0.8158844765342961, 'agreement': 0.23487544483985764, 'direct_attack': 0.26993865030674846, 'undercutter_attack': 0.19883040935672514, 'partial': 0.0379746835443038}, 'f1': {'support': 0.7786391042204995, 'agreement': 0.32273838630806845, 'direct_attack': 0.23848238482384823, 'undercutter_attack': 0.17346938775510204, 'partial': 0.05357142857142857}, 'support': {'support': 1108, 'agreement': 281, 'direct_attack': 163, 'undercutter_attack': 171, 'partial': 79}, 'micro_avg': {'precision': 0.5832408435072142, 'recall': 0.5832408435072142, 'f1': 0.5832408435072142, 'support': None}, 'macro_avg': {'precision': 0.3437236553552971, 'recall': 0.31150073291638625, 'f1': 0.31338013833578937, 'support': None}, 'weighted_avg': {'precision': 0.576172705202481, 'recall': 0.5832408435072142, 'f1': 0.5694726142721606, 'support': None}}
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9940e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3400e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5350e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1798e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6760e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6428e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8700e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6379e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6882e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 11---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7443181818181818, 'agreement': 0.5028248587570622, 'direct_attack': 0.21379310344827587, 'undercutter_attack': 0.1590909090909091, 'partial': 0.08333333333333333}, 'recall': {'support': 0.8276173285198556, 'agreement': 0.3167259786476868, 'direct_attack': 0.1901840490797546, 'undercutter_attack': 0.16374269005847952, 'partial': 0.0759493670886076}, 'f1': {'support': 0.7837606837606836, 'agreement': 0.388646288209607, 'direct_attack': 0.20129870129870134, 'undercutter_attack': 0.16138328530259366, 'partial': 0.07947019867549669}, 'support': {'support': 1108, 'agreement': 281, 'direct_attack': 163, 'undercutter_attack': 171, 'partial': 79}, 'micro_avg': {'precision': 0.5943396226415094, 'recall': 0.5943396226415094, 'f1': 0.5943396226415094, 'support': None}, 'macro_avg': {'precision': 0.34067207728955246, 'recall': 0.3148438826788768, 'f1': 0.32291183144941643, 'support': None}, 'weighted_avg': {'precision': 0.5741589819174404, 'recall': 0.5943396226415094, 'f1': 0.5795243176401405, 'support': None}}
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4784e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2311e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9768e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4128e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5035e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0627e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8274e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3372e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0421e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8598e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8761e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8912e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9788e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0750, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9565e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3815e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3736e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 12---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.741112828438949, 'agreement': 0.5454545454545454, 'direct_attack': 0.21428571428571427, 'undercutter_attack': 0.14606741573033707, 'partial': 0.09090909090909091}, 'recall': {'support': 0.8655234657039711, 'agreement': 0.23487544483985764, 'direct_attack': 0.20245398773006135, 'undercutter_attack': 0.15204678362573099, 'partial': 0.06329113924050633}, 'f1': {'support': 0.7985012489592006, 'agreement': 0.32835820895522383, 'direct_attack': 0.2082018927444795, 'undercutter_attack': 0.14899713467048709, 'partial': 0.07462686567164178}, 'support': {'support': 1108, 'agreement': 281, 'direct_attack': 163, 'undercutter_attack': 171, 'partial': 79}, 'micro_avg': {'precision': 0.6043285238623751, 'recall': 0.6043285238623751, 'f1': 0.6043285238623751, 'support': None}, 'macro_avg': {'precision': 0.3475659189637273, 'recall': 0.3036381642280254, 'f1': 0.3117370702002066, 'support': None}, 'weighted_avg': {'precision': 0.5779765032649057, 'recall': 0.6043285238623751, 'f1': 0.5784234081560906, 'support': None}}
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2147e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7144e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8144e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4318e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8335e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3079e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9375e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1262e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5551e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3017e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3785e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7054e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9294e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1545e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8426e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6530e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4844e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9839e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6206e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8426e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0360e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2040e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2934e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5045e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0082e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2743e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6852e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5822e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4229e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6066e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0672e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0636e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6318e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6357e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4309e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5568e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4500e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1011e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 13---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7479674796747967, 'agreement': 0.5609756097560976, 'direct_attack': 0.22972972972972974, 'undercutter_attack': 0.15025906735751296, 'partial': 0.08955223880597014}, 'recall': {'support': 0.8303249097472925, 'agreement': 0.3274021352313167, 'direct_attack': 0.2085889570552147, 'undercutter_attack': 0.1695906432748538, 'partial': 0.0759493670886076}, 'f1': {'support': 0.7869974337040206, 'agreement': 0.41348314606741576, 'direct_attack': 0.21864951768488744, 'undercutter_attack': 0.15934065934065933, 'partial': 0.0821917808219178}, 'support': {'support': 1108, 'agreement': 281, 'direct_attack': 163, 'undercutter_attack': 171, 'partial': 79}, 'micro_avg': {'precision': 0.5998890122086571, 'recall': 0.5998890122086571, 'f1': 0.5998890122086571, 'support': None}, 'macro_avg': {'precision': 0.3556968250648215, 'recall': 0.32237120247945705, 'f1': 0.33213250752378015, 'support': None}, 'weighted_avg': {'precision': 0.5863468297174753, 'recall': 0.5998890122086571, 'f1': 0.5868824613783683, 'support': None}}
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9637e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3669e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8286e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6137e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9534e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5247e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1707e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6143e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1009e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8847e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0182e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5256e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2664e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6325e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4387e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1362e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9819e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4651e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7972e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3221e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6003e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8559e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9022e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3845e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6931e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1079e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8125e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2595e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3531e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3360e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8983e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3784e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1342e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9658e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0049e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8223e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7385e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1472e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3197e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3472e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5023e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9374e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8729e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3064e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9264e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8277e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3984e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6185e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7265e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8447e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5855e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 14---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7454844006568144, 'agreement': 0.519774011299435, 'direct_attack': 0.2446043165467626, 'undercutter_attack': 0.14646464646464646, 'partial': 0.08571428571428572}, 'recall': {'support': 0.8194945848375451, 'agreement': 0.3274021352313167, 'direct_attack': 0.2085889570552147, 'undercutter_attack': 0.1695906432748538, 'partial': 0.0759493670886076}, 'f1': {'support': 0.7807394668959587, 'agreement': 0.4017467248908297, 'direct_attack': 0.2251655629139073, 'undercutter_attack': 0.15718157181571815, 'partial': 0.08053691275167786}, 'support': {'support': 1108, 'agreement': 281, 'direct_attack': 163, 'undercutter_attack': 171, 'partial': 79}, 'micro_avg': {'precision': 0.5932297447280799, 'recall': 0.5932297447280799, 'f1': 0.5932297447280799, 'support': None}, 'macro_avg': {'precision': 0.3484083321363888, 'recall': 0.32020513749750756, 'f1': 0.3290740478536184, 'support': None}, 'weighted_avg': {'precision': 0.579212319543228, 'recall': 0.5932297447280799, 'f1': 0.5815164321075932, 'support': None}}
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6590e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9091e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6509e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1504e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4518e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4681e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8132e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3824e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8133e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5639e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8589e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8334e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8425e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9746e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8334e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7760e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1099e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7618e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3591e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8819e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1898e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2251e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7224e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0766e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2462e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9306e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4167e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7005e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0494e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8446e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7951e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4420e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3752e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2004e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6943e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1701e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8384e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3260e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6761e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4410e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9728e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6628e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7860e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4139e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1610e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6730e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4117e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 15---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7459150326797386, 'agreement': 0.5168539325842697, 'direct_attack': 0.24087591240875914, 'undercutter_attack': 0.14871794871794872, 'partial': 0.08823529411764706}, 'recall': {'support': 0.8240072202166066, 'agreement': 0.3274021352313167, 'direct_attack': 0.20245398773006135, 'undercutter_attack': 0.1695906432748538, 'partial': 0.0759493670886076}, 'f1': {'support': 0.7830188679245282, 'agreement': 0.40087145969498916, 'direct_attack': 0.22000000000000003, 'undercutter_attack': 0.15846994535519127, 'partial': 0.0816326530612245}, 'support': {'support': 1108, 'agreement': 281, 'direct_attack': 163, 'undercutter_attack': 171, 'partial': 79}, 'micro_avg': {'precision': 0.595449500554939, 'recall': 0.595449500554939, 'f1': 0.595449500554939, 'support': None}, 'macro_avg': {'precision': 0.3481196241016726, 'recall': 0.3198806707082892, 'f1': 0.32879858520718663, 'support': None}, 'weighted_avg': {'precision': 0.5790088470888021, 'recall': 0.595449500554939, 'f1': 0.5824845316771607, 'support': None}}
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0201e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1160e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6498e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7577e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4002e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0545e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7545e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4054e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8212e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3440e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6355e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5340e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1423e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0757e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3644e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5274e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2238e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3016e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7043e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7367e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4339e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1208e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1625e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1958e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9625e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6295e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2964e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9997e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5962e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5268e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8232e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6266e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8416e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5994e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9851e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1393e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3882e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7921e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2501e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6127e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4175e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0140e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0836e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2474e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5197e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2622e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2522e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1974e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8577e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0544e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1632e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7160e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6309e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0375e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6074e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4472e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0745e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8065e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9413e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2341e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 16---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.743298131600325, 'agreement': 0.5303867403314917, 'direct_attack': 0.2462686567164179, 'undercutter_attack': 0.1443850267379679, 'partial': 0.10144927536231885}, 'recall': {'support': 0.825812274368231, 'agreement': 0.3416370106761566, 'direct_attack': 0.20245398773006135, 'undercutter_attack': 0.15789473684210525, 'partial': 0.08860759493670886}, 'f1': {'support': 0.7823856348867038, 'agreement': 0.41558441558441556, 'direct_attack': 0.2222222222222222, 'undercutter_attack': 0.15083798882681565, 'partial': 0.0945945945945946}, 'support': {'support': 1108, 'agreement': 281, 'direct_attack': 163, 'undercutter_attack': 171, 'partial': 79}, 'micro_avg': {'precision': 0.5982241953385128, 'recall': 0.5982241953385128, 'f1': 0.5982241953385128, 'support': None}, 'macro_avg': {'precision': 0.3531575661497043, 'recall': 0.32328112091065264, 'f1': 0.3331249712229503, 'support': None}, 'weighted_avg': {'precision': 0.5801659973456721, 'recall': 0.5982241953385128, 'f1': 0.5844345147160206, 'support': None}}
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9194e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5598e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4660e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7021e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7577e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7681e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5299e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4469e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2943e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5570e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3431e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6487e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4620e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6578e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0888e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6339e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5378e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6165e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3905e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3329e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8014e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6256e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6749e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0818e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7205e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3793e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8920e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3984e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1552e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6597e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1807e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4530e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6043e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0492e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6515e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9637e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7024e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1130e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0625e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3046e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3603e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0110e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4033e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0252e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2888e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6597e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6265e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7426e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0918e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6218e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4347e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9141e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3834e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1069e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2873e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3471e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9543e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1442e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2623e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2169e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2361e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5335e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1272e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0899e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5205e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1398e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0708e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5680e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0252e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5005e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2411e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5803e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8759e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3176e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5516e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1865e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 17---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7425101214574898, 'agreement': 0.5248618784530387, 'direct_attack': 0.25190839694656486, 'undercutter_attack': 0.14594594594594595, 'partial': 0.1}, 'recall': {'support': 0.8276173285198556, 'agreement': 0.33807829181494664, 'direct_attack': 0.20245398773006135, 'undercutter_attack': 0.15789473684210525, 'partial': 0.08860759493670886}, 'f1': {'support': 0.782757148954332, 'agreement': 0.41125541125541126, 'direct_attack': 0.22448979591836735, 'undercutter_attack': 0.15168539325842698, 'partial': 0.09395973154362416}, 'support': {'support': 1108, 'agreement': 281, 'direct_attack': 163, 'undercutter_attack': 171, 'partial': 79}, 'micro_avg': {'precision': 0.5987791342952276, 'recall': 0.5987791342952276, 'f1': 0.5987791342952276, 'support': None}, 'macro_avg': {'precision': 0.35304526856060786, 'recall': 0.3229303879687355, 'f1': 0.3328294961860324, 'support': None}, 'weighted_avg': {'precision': 0.5794146658597389, 'recall': 0.5987791342952276, 'f1': 0.584245587890123, 'support': None}}
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4681e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6052e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4084e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4547e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3691e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7627e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4128e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6863e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7960e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0854e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2097e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8718e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5822e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1202e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8000e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6103e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0036e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2004e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0091e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1676e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1089e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3269e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7154e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4734e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5934e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7587e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3584e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6860e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6407e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8646e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8144e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7155e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2752e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9534e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1602e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3358e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1717e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9767e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7856e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9525e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9794e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2158e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4941e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0784e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0534e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1534e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1645e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3328e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9433e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4097e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6539e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0695e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1792e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4956e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1277e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0233e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0465e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1895e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7681e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3885e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2977e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6789e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7781e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3442e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0676e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8676e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1450e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0887e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0694e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2785e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8777e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9425e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7886e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5417e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5486e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7015e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6476e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1965e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0433e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7596e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3945e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8132e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3578e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5650e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4632e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2640e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3977e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1866e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 18---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7420924574209246, 'agreement': 0.5080213903743316, 'direct_attack': 0.24427480916030533, 'undercutter_attack': 0.143646408839779, 'partial': 0.1}, 'recall': {'support': 0.825812274368231, 'agreement': 0.33807829181494664, 'direct_attack': 0.19631901840490798, 'undercutter_attack': 0.15204678362573099, 'partial': 0.08860759493670886}, 'f1': {'support': 0.7817172148654422, 'agreement': 0.405982905982906, 'direct_attack': 0.21768707482993196, 'undercutter_attack': 0.14772727272727273, 'partial': 0.09395973154362416}, 'support': {'support': 1108, 'agreement': 281, 'direct_attack': 163, 'undercutter_attack': 171, 'partial': 79}, 'micro_avg': {'precision': 0.5965593784683685, 'recall': 0.5965593784683685, 'f1': 0.5965593784683685, 'support': None}, 'macro_avg': {'precision': 0.3476070131590681, 'recall': 0.3201727926301051, 'f1': 0.32941483998983545, 'support': None}, 'weighted_avg': {'precision': 0.5756230762054959, 'recall': 0.5965593784683685, 'f1': 0.5817930334504414, 'support': None}}
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7251e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1390e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6881e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6022e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7024e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7156e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5035e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7039e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2007e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3278e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6386e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2065e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6930e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7314e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5854e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8901e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8829e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8689e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7478e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0009e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7630e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5630e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8801e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1017e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7627e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7859e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5247e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6246e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2480e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6424e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6628e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7630e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6355e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0615e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0564e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1653e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6972e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6521e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0133e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6630e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1726e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0221e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0914e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7578e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8486e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2118e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9906e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4277e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9210e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8234e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2492e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0866e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0581e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2852e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7125e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9110e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9854e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5516e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6337e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4762e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9315e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0121e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3630e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4623e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4124e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5429e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3592e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5055e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8816e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6689e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2519e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7950e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5035e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5037e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2782e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6630e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4257e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0031e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2370e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8558e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2474e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9758e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8041e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7536e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8858e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9394e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6165e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8604e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6103e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7022e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5046e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9231e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1247e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4629e-05, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 19---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7422764227642277, 'agreement': 0.5, 'direct_attack': 0.24242424242424243, 'undercutter_attack': 0.14606741573033707, 'partial': 0.09722222222222222}, 'recall': {'support': 0.8240072202166066, 'agreement': 0.33807829181494664, 'direct_attack': 0.19631901840490798, 'undercutter_attack': 0.15204678362573099, 'partial': 0.08860759493670886}, 'f1': {'support': 0.7810094097519248, 'agreement': 0.4033970276008493, 'direct_attack': 0.2169491525423729, 'undercutter_attack': 0.14899713467048709, 'partial': 0.09271523178807946}, 'support': {'support': 1108, 'agreement': 281, 'direct_attack': 163, 'undercutter_attack': 171, 'partial': 79}, 'micro_avg': {'precision': 0.595449500554939, 'recall': 0.595449500554939, 'f1': 0.595449500554939, 'support': None}, 'macro_avg': {'precision': 0.34559806062820586, 'recall': 0.3198117817997802, 'f1': 0.32861359127074274, 'support': None}, 'weighted_avg': {'precision': 0.5744259220773357, 'recall': 0.595449500554939, 'f1': 0.5809537824446668, 'support': None}}
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5486e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9564e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5629e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3550e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0523e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3098e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8728e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4371e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8901e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6274e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9639e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5122e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2428e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4075e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9789e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6722e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4218e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0372e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3306e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9491e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1108e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4465e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6054e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6394e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9918e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8296e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7396e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6303e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5096e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0814e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0754e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4146e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4371e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3512e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5874e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8423e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3734e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3923e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6739e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0724e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2343e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8202e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1423e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9948e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8659e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1368e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3902e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3471e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0403e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6791e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4640e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4510e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6909e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6425e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2218e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0646e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0109e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0708e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0586e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8497e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0149e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2107e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1048e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4803e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8999e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3198e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0958e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3927e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2795e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1078e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5885e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7496e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6083e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0826e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4214e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0523e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2441e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9322e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2652e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1359e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8246e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1492e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6043e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8616e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8362e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1747e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4529e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6267e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9525e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5831e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9776e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7406e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6609e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9979e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5014e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5005e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3440e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3661e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 20---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7428803905614321, 'agreement': 0.49222797927461137, 'direct_attack': 0.2440944881889764, 'undercutter_attack': 0.14917127071823205, 'partial': 0.09722222222222222}, 'recall': {'support': 0.8240072202166066, 'agreement': 0.33807829181494664, 'direct_attack': 0.1901840490797546, 'undercutter_attack': 0.15789473684210525, 'partial': 0.08860759493670886}, 'f1': {'support': 0.7813436029097133, 'agreement': 0.4008438818565401, 'direct_attack': 0.21379310344827587, 'undercutter_attack': 0.1534090909090909, 'partial': 0.09271523178807946}, 'support': {'support': 1108, 'agreement': 281, 'direct_attack': 163, 'undercutter_attack': 171, 'partial': 79}, 'micro_avg': {'precision': 0.595449500554939, 'recall': 0.595449500554939, 'f1': 0.595449500554939, 'support': None}, 'macro_avg': {'precision': 0.34511927019309485, 'recall': 0.3197543785780244, 'f1': 0.3284209821823399, 'support': None}, 'weighted_avg': {'precision': 0.5740309541295278, 'recall': 0.5954495005549391, 'f1': 0.580894326606233, 'support': None}}
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9516e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8634e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9063e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7233e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7233e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6994e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6113e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9915e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0451e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7618e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9103e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9394e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0796e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7235e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0672e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5861e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8795e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1904e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8687e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1230e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6570e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6275e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1844e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4802e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5084e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9222e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3003e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1679e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7212e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9969e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5995e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6758e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4571e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2440e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5670e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9948e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4729e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4123e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5225e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2463e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0757e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6478e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5128e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0444e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7250e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0100e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8556e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6669e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7386e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0754e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0490e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3016e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0309e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2622e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2686e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5377e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6061e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8558e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7878e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4924e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8242e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8304e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1341e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4401e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4495e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1913e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4882e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5183e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2973e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1550e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4945e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7233e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4379e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3548e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9491e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4054e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4859e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6305e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4742e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3936e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9253e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3281e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4002e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3349e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3197e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0675e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7941e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1390e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8059e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5619e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7929e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1904e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2328e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3247e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4572e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6850e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2988e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0161e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3470e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8686e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0839e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0823e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1199e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6766e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2038e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8847e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0460e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9533e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4428e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5153e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)


		-------------RUN 3-----------
			------------EPOCH 1---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.0, 'agreement': 0.1472239550842171, 'direct_attack': 0.0, 'undercutter_attack': 0.0, 'partial': 0.0}, 'recall': {'support': 0.0, 'agreement': 1.0, 'direct_attack': 0.0, 'undercutter_attack': 0.0, 'partial': 0.0}, 'f1': {'support': 0.0, 'agreement': 0.25666122892876564, 'direct_attack': 0.0, 'undercutter_attack': 0.0, 'partial': 0.0}, 'support': {'support': 1028, 'agreement': 236, 'direct_attack': 122, 'undercutter_attack': 135, 'partial': 83}, 'micro_avg': {'precision': 0.14713216957605985, 'recall': 0.14713216957605985, 'f1': 0.14713216957605985, 'support': None}, 'macro_avg': {'precision': 0.02944479101684342, 'recall': 0.2, 'f1': 0.05133224578575313, 'support': None}, 'weighted_avg': {'precision': 0.021661379925109248, 'recall': 0.14713216957605985, 'f1': 0.037763123458347064, 'support': None}}
Loss: tensor(2.4690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8873, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4774, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4632, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3915, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3738, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2796, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7922, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8791, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9947, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7652, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6955, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1844, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1817, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7955, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9998, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7560, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8844, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7769, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3837, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3971, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9739, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0806, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6757, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3714, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5837, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0983, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6794, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8719, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4765, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7750, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7971, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7801, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3694, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7765, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7680, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6843, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1765, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4481, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2601, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0940, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7662, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0701, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8481, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0660, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9977, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3652, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9616, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7511, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7940, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3868, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0654, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1873, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9956, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6935, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7921, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5844, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3987, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7801, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5632, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7662, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4862, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6935, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7709, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 2---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7985948477751756, 'agreement': 0.42955326460481097, 'direct_attack': 0.11363636363636363, 'undercutter_attack': 0.0951683748169839, 'partial': 0.028169014084507043}, 'recall': {'support': 0.3317120622568093, 'agreement': 0.5296610169491526, 'direct_attack': 0.12295081967213115, 'undercutter_attack': 0.48148148148148145, 'partial': 0.024096385542168676}, 'f1': {'support': 0.46872852233676976, 'agreement': 0.4743833017077799, 'direct_attack': 0.11811023622047244, 'undercutter_attack': 0.15892420537897312, 'partial': 0.025974025974025976}, 'support': {'support': 1028, 'agreement': 236, 'direct_attack': 122, 'undercutter_attack': 135, 'partial': 83}, 'micro_avg': {'precision': 0.341645885286783, 'recall': 0.341645885286783, 'f1': 0.341645885286783, 'support': None}, 'macro_avg': {'precision': 0.2930243729835682, 'recall': 0.29798035318034866, 'f1': 0.24922405832360428, 'support': None}, 'weighted_avg': {'precision': 0.5931293448207975, 'recall': 0.341645885286783, 'f1': 0.3939073820861213, 'support': None}}
Loss: tensor(2.1787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6950, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4632, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1806, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0713, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4955, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8837, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6898, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5744, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6773, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4680, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0978, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4947, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5662, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6985, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0921, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3740, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2720, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8604, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2898, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6950, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9754, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4912, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1694, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8837, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2791, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6847, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0560, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4873, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4831, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4868, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5740, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3868, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3998, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0972, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0751, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6738, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2773, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6632, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2641, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6813, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2972, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9769, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6972, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9994, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3739, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0903, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5947, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0750, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1862, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7950, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1840, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5796, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3751, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5801, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0926, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2671, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6997, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4797, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5985, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3840, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2956, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2657, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 3---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8867924528301887, 'agreement': 0.5185185185185185, 'direct_attack': 0.12974683544303797, 'undercutter_attack': 0.08015768725361366, 'partial': 0.109375}, 'recall': {'support': 0.27405247813411077, 'agreement': 0.17796610169491525, 'direct_attack': 0.3360655737704918, 'undercutter_attack': 0.4552238805970149, 'partial': 0.1686746987951807}, 'f1': {'support': 0.41870824053452116, 'agreement': 0.26498422712933756, 'direct_attack': 0.1872146118721461, 'undercutter_attack': 0.13631284916201117, 'partial': 0.13270142180094788}, 'support': {'support': 1029, 'agreement': 236, 'direct_attack': 122, 'undercutter_attack': 134, 'partial': 83}, 'micro_avg': {'precision': 0.2743142144638404, 'recall': 0.2743142144638404, 'f1': 0.2743142144638404, 'support': None}, 'macro_avg': {'precision': 0.34491809880907176, 'recall': 0.2823965465983426, 'f1': 0.22798427009979277, 'support': None}, 'weighted_avg': {'precision': 0.6674115793944324, 'recall': 0.2743142144638404, 'f1': 0.34009188251754113, 'support': None}}
Loss: tensor(0.1990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1641, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4860, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9813, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5794, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0641, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5927, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6862, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3956, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0950, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0739, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1769, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4784, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6769, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4860, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1998, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2773, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1774, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0751, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5374, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2971, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3957, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0616, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0940, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7900, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5903, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2569, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0904, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0680, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2740, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3739, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2714, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4785, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1784, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0880, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1965, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2632, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0913, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3929, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1662, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1427, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0713, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1569, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6730, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8935, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0880, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3783, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0884, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 4---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8118393234672304, 'agreement': 0.4666666666666667, 'direct_attack': 0.14527027027027026, 'undercutter_attack': 0.09417040358744394, 'partial': 0.15789473684210525}, 'recall': {'support': 0.7470817120622568, 'agreement': 0.23728813559322035, 'direct_attack': 0.3524590163934426, 'undercutter_attack': 0.15555555555555556, 'partial': 0.03614457831325301}, 'f1': {'support': 0.778115501519757, 'agreement': 0.3146067415730337, 'direct_attack': 0.20574162679425836, 'undercutter_attack': 0.11731843575418993, 'partial': 0.0588235294117647}, 'support': {'support': 1028, 'agreement': 236, 'direct_attack': 122, 'undercutter_attack': 135, 'partial': 83}, 'micro_avg': {'precision': 0.5554862842892768, 'recall': 0.5554862842892768, 'f1': 0.5554862842892768, 'support': None}, 'macro_avg': {'precision': 0.3351682801667433, 'recall': 0.3057057995835457, 'f1': 0.2949211670106007, 'support': None}, 'weighted_avg': {'precision': 0.6161130913172188, 'recall': 0.5554862842892768, 'f1': 0.5735478471386768, 'support': None}}
Loss: tensor(0.2061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1654, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3751, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2680, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0935, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0693, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4801, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7739, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0926, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0560, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3890, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2660, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0705, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2956, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1662, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0654, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3601, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0569, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0680, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3903, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7874, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0720, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2641, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0840, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1935, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8987, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4784, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0906, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0906, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0847, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0874, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4915, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2926, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 5---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.8118811881188119, 'agreement': 0.4065040650406504, 'direct_attack': 0.1590909090909091, 'undercutter_attack': 0.1067193675889328, 'partial': 0.3181818181818182}, 'recall': {'support': 0.7178988326848249, 'agreement': 0.211864406779661, 'direct_attack': 0.05737704918032787, 'undercutter_attack': 0.4, 'partial': 0.08433734939759036}, 'f1': {'support': 0.7620030975735675, 'agreement': 0.27855153203342614, 'direct_attack': 0.08433734939759036, 'undercutter_attack': 0.16848673946957882, 'partial': 0.13333333333333333}, 'support': {'support': 1028, 'agreement': 236, 'direct_attack': 122, 'undercutter_attack': 135, 'partial': 83}, 'micro_avg': {'precision': 0.5336658354114713, 'recall': 0.5336658354114713, 'f1': 0.5336658354114713, 'support': None}, 'macro_avg': {'precision': 0.3604754696042245, 'recall': 0.2942955276084808, 'f1': 0.2853424103614992, 'support': None}, 'weighted_avg': {'precision': 0.6176895992384163, 'recall': 0.5336658354114713, 'f1': 0.5568446876478067, 'support': None}}
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1701, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6750, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0773, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0806, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0751, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0654, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0705, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0660, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0783, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0560, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3783, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0714, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2913, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0940, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0560, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0481, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 6---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.779646017699115, 'agreement': 0.5263157894736842, 'direct_attack': 0.2116788321167883, 'undercutter_attack': 0.11570247933884298, 'partial': 0.10526315789473684}, 'recall': {'support': 0.8561710398445093, 'agreement': 0.1694915254237288, 'direct_attack': 0.23770491803278687, 'undercutter_attack': 0.2074074074074074, 'partial': 0.024390243902439025}, 'f1': {'support': 0.8161185734136174, 'agreement': 0.2564102564102564, 'direct_attack': 0.2239382239382239, 'undercutter_attack': 0.1485411140583554, 'partial': 0.039603960396039604}, 'support': {'support': 1029, 'agreement': 236, 'direct_attack': 122, 'undercutter_attack': 135, 'partial': 82}, 'micro_avg': {'precision': 0.6109725685785536, 'recall': 0.6109725685785536, 'f1': 0.6109725685785536, 'support': None}, 'macro_avg': {'precision': 0.3477212553046335, 'recall': 0.29903302692217426, 'f1': 0.29692242564329857, 'support': None}, 'weighted_avg': {'precision': 0.6088170260003362, 'recall': 0.6109725685785536, 'f1': 0.5928428123605045, 'support': None}}
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1852, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0994, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0694, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0632, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1765, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1965, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6950, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0713, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0511, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3785, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1481, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0362, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 7---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7911275415896488, 'agreement': 0.48623853211009177, 'direct_attack': 0.21138211382113822, 'undercutter_attack': 0.10970464135021098, 'partial': 0.07547169811320754}, 'recall': {'support': 0.8318756073858115, 'agreement': 0.2245762711864407, 'direct_attack': 0.21311475409836064, 'undercutter_attack': 0.19402985074626866, 'partial': 0.04819277108433735}, 'f1': {'support': 0.8109900521080058, 'agreement': 0.3072463768115942, 'direct_attack': 0.21224489795918366, 'undercutter_attack': 0.14016172506738547, 'partial': 0.058823529411764705}, 'support': {'support': 1029, 'agreement': 236, 'direct_attack': 122, 'undercutter_attack': 134, 'partial': 83}, 'micro_avg': {'precision': 0.6016209476309227, 'recall': 0.6016209476309227, 'f1': 0.6016209476309227, 'support': None}, 'macro_avg': {'precision': 0.33478490539685946, 'recall': 0.30235785090024375, 'f1': 0.3058933162715868, 'support': None}, 'weighted_avg': {'precision': 0.6082142921722155, 'recall': 0.6016209476309227, 'f1': 0.5963695824176438, 'support': None}}
Loss: tensor(0.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2652, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5693, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 8---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7806167400881058, 'agreement': 0.5138888888888888, 'direct_attack': 0.19327731092436976, 'undercutter_attack': 0.1013215859030837, 'partial': 0.11764705882352941}, 'recall': {'support': 0.8618677042801557, 'agreement': 0.15677966101694915, 'direct_attack': 0.1885245901639344, 'undercutter_attack': 0.17037037037037037, 'partial': 0.07228915662650602}, 'f1': {'support': 0.8192325473878873, 'agreement': 0.24025974025974023, 'direct_attack': 0.19087136929460582, 'undercutter_attack': 0.1270718232044199, 'partial': 0.08955223880597016}, 'support': {'support': 1028, 'agreement': 236, 'direct_attack': 122, 'undercutter_attack': 135, 'partial': 83}, 'micro_avg': {'precision': 0.60785536159601, 'recall': 0.60785536159601, 'f1': 0.60785536159601, 'support': None}, 'macro_avg': {'precision': 0.3413503169255955, 'recall': 0.2899662964915831, 'f1': 0.2933975437905247, 'support': None}, 'weighted_avg': {'precision': 0.6052211586660804, 'recall': 0.60785536159601, 'f1': 0.5902407708375816, 'support': None}}
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 9---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7894257064721969, 'agreement': 0.4835164835164835, 'direct_attack': 0.17424242424242425, 'undercutter_attack': 0.1134453781512605, 'partial': 0.10869565217391304}, 'recall': {'support': 0.8424124513618677, 'agreement': 0.1864406779661017, 'direct_attack': 0.1885245901639344, 'undercutter_attack': 0.2, 'partial': 0.060240963855421686}, 'f1': {'support': 0.8150588235294117, 'agreement': 0.26911314984709483, 'direct_attack': 0.18110236220472442, 'undercutter_attack': 0.1447721179624665, 'partial': 0.07751937984496123}, 'support': {'support': 1028, 'agreement': 236, 'direct_attack': 122, 'undercutter_attack': 135, 'partial': 83}, 'micro_avg': {'precision': 0.6016209476309227, 'recall': 0.6016209476309227, 'f1': 0.6016209476309227, 'support': None}, 'macro_avg': {'precision': 0.33386512891125564, 'recall': 0.2955237366694651, 'f1': 0.29751316667773176, 'support': None}, 'weighted_avg': {'precision': 0.6055074546768948, 'recall': 0.6016209476309227, 'f1': 0.5919351662052311, 'support': None}}
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5813, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1767e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8791e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 10---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7871024734982333, 'agreement': 0.48514851485148514, 'direct_attack': 0.22, 'undercutter_attack': 0.11353711790393013, 'partial': 0.11904761904761904}, 'recall': {'support': 0.8658892128279884, 'agreement': 0.2076271186440678, 'direct_attack': 0.18181818181818182, 'undercutter_attack': 0.1925925925925926, 'partial': 0.060240963855421686}, 'f1': {'support': 0.8246182322998611, 'agreement': 0.29080118694362017, 'direct_attack': 0.19909502262443438, 'undercutter_attack': 0.14285714285714285, 'partial': 0.08}, 'support': {'support': 1029, 'agreement': 236, 'direct_attack': 121, 'undercutter_attack': 135, 'partial': 83}, 'micro_avg': {'precision': 0.6190773067331671, 'recall': 0.6190773067331671, 'f1': 0.6190773067331671, 'support': None}, 'macro_avg': {'precision': 0.3449671450602535, 'recall': 0.3016336139476505, 'f1': 0.3074743169450117, 'support': None}, 'weighted_avg': {'precision': 0.6086358840602341, 'recall': 0.6190773067331671, 'f1': 0.6029784620813731, 'support': None}}
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8256e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4220e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 11---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7904085257548845, 'agreement': 0.49019607843137253, 'direct_attack': 0.21153846153846154, 'undercutter_attack': 0.11403508771929824, 'partial': 0.11363636363636363}, 'recall': {'support': 0.8649173955296404, 'agreement': 0.2127659574468085, 'direct_attack': 0.18032786885245902, 'undercutter_attack': 0.1925925925925926, 'partial': 0.060240963855421686}, 'f1': {'support': 0.8259860788863108, 'agreement': 0.29673590504451036, 'direct_attack': 0.19469026548672566, 'undercutter_attack': 0.14325068870523416, 'partial': 0.07874015748031496}, 'support': {'support': 1029, 'agreement': 235, 'direct_attack': 122, 'undercutter_attack': 135, 'partial': 83}, 'micro_avg': {'precision': 0.6190773067331671, 'recall': 0.6190773067331671, 'f1': 0.6190773067331671, 'support': None}, 'macro_avg': {'precision': 0.34396290341607605, 'recall': 0.3021689556553845, 'f1': 0.3078806191206192, 'support': None}, 'weighted_avg': {'precision': 0.6104493134443668, 'recall': 0.6190773067331671, 'f1': 0.6043011853459644, 'support': None}}
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1020e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 12---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7859030837004405, 'agreement': 0.5176470588235295, 'direct_attack': 0.19672131147540983, 'undercutter_attack': 0.1141552511415525, 'partial': 0.11627906976744186}, 'recall': {'support': 0.867704280155642, 'agreement': 0.1864406779661017, 'direct_attack': 0.19672131147540983, 'undercutter_attack': 0.18518518518518517, 'partial': 0.060240963855421686}, 'f1': {'support': 0.8247803975959315, 'agreement': 0.27414330218068533, 'direct_attack': 0.1967213114754098, 'undercutter_attack': 0.14124293785310735, 'partial': 0.07936507936507936}, 'support': {'support': 1028, 'agreement': 236, 'direct_attack': 122, 'undercutter_attack': 135, 'partial': 83}, 'micro_avg': {'precision': 0.6172069825436409, 'recall': 0.6172069825436409, 'f1': 0.6172069825436409, 'support': None}, 'macro_avg': {'precision': 0.3461411549816748, 'recall': 0.2992584837275521, 'f1': 0.3032506056940426, 'support': None}, 'weighted_avg': {'precision': 0.6104334149758186, 'recall': 0.6172069825436409, 'f1': 0.5998922482797571, 'support': None}}
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9185e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1701, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1593e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3724e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1465e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8749e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7649e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9214e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4402e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2776e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4330e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4611e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4802e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7802e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8065e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6409e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5036e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6914e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 13---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7876651982378855, 'agreement': 0.5051546391752577, 'direct_attack': 0.2169811320754717, 'undercutter_attack': 0.11261261261261261, 'partial': 0.11363636363636363}, 'recall': {'support': 0.8688046647230321, 'agreement': 0.2076271186440678, 'direct_attack': 0.1885245901639344, 'undercutter_attack': 0.18518518518518517, 'partial': 0.06097560975609756}, 'f1': {'support': 0.8262476894639558, 'agreement': 0.29429429429429427, 'direct_attack': 0.20175438596491227, 'undercutter_attack': 0.14005602240896356, 'partial': 0.07936507936507936}, 'support': {'support': 1029, 'agreement': 236, 'direct_attack': 122, 'undercutter_attack': 135, 'partial': 82}, 'micro_avg': {'precision': 0.6209476309226932, 'recall': 0.6209476309226932, 'f1': 0.6209476309226932, 'support': None}, 'macro_avg': {'precision': 0.3472099891475182, 'recall': 0.3022234336944634, 'f1': 0.308343494299441, 'support': None}, 'weighted_avg': {'precision': 0.6114193057769558, 'recall': 0.6209476309226932, 'f1': 0.6045460477136719, 'support': None}}
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0021e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5854e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2776e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6873e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1465e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4490e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3009e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5226e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3130e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3876e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4956e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2583e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7398e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0818e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 14---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7837837837837838, 'agreement': 0.4954954954954955, 'direct_attack': 0.23404255319148937, 'undercutter_attack': 0.12857142857142856, 'partial': 0.11904761904761904}, 'recall': {'support': 0.8745136186770428, 'agreement': 0.2330508474576271, 'direct_attack': 0.18032786885245902, 'undercutter_attack': 0.2, 'partial': 0.060240963855421686}, 'f1': {'support': 0.8266666666666667, 'agreement': 0.31700288184438036, 'direct_attack': 0.20370370370370372, 'undercutter_attack': 0.15652173913043477, 'partial': 0.08}, 'support': {'support': 1028, 'agreement': 236, 'direct_attack': 122, 'undercutter_attack': 135, 'partial': 83}, 'micro_avg': {'precision': 0.628428927680798, 'recall': 0.628428927680798, 'f1': 0.628428927680798, 'support': None}, 'macro_avg': {'precision': 0.35218817601796326, 'recall': 0.3096266597685101, 'f1': 0.3167789982690371, 'support': None}, 'weighted_avg': {'precision': 0.6100111928891044, 'recall': 0.628428927680798, 'f1': 0.6092570449395683, 'support': None}}
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4309e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7972e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7893e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0042e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0191e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8911e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6025e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7651e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5823e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7620e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8296e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6095e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0173e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6175e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9758e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6671, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6882e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6581e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5570e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9639e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9819e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4147e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5844e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5259e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5096e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8335e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 15---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7835497835497836, 'agreement': 0.5301204819277109, 'direct_attack': 0.23148148148148148, 'undercutter_attack': 0.11981566820276497, 'partial': 0.0975609756097561}, 'recall': {'support': 0.8794946550048591, 'agreement': 0.18723404255319148, 'direct_attack': 0.20491803278688525, 'undercutter_attack': 0.1925925925925926, 'partial': 0.04819277108433735}, 'f1': {'support': 0.8287545787545788, 'agreement': 0.2767295597484277, 'direct_attack': 0.21739130434782608, 'undercutter_attack': 0.14772727272727273, 'partial': 0.06451612903225806}, 'support': {'support': 1029, 'agreement': 235, 'direct_attack': 122, 'undercutter_attack': 135, 'partial': 83}, 'micro_avg': {'precision': 0.6259351620947631, 'recall': 0.6259351620947631, 'f1': 0.6259351620947631, 'support': None}, 'macro_avg': {'precision': 0.35250567815429934, 'recall': 0.3024864188043731, 'f1': 0.30702376892207267, 'support': None}, 'weighted_avg': {'precision': 0.6130701106293411, 'recall': 0.6259351620947631, 'f1': 0.6045135085646111, 'support': None}}
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3957e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7681e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0838e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3279e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6904, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1263e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2434e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1876e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9425e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8587e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8791e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3228e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2180e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2826e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5238e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8942e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0375e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4894e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4652e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9233e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7015e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9849e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2816e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0829e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6388e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9113e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1223e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2977e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8598e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9386e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7133e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9365e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6954e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2029e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6912e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6437e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4629e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1787e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9080e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4632e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7276e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0797e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 16---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7763605442176871, 'agreement': 0.4838709677419355, 'direct_attack': 0.273972602739726, 'undercutter_attack': 0.14136125654450263, 'partial': 0.1}, 'recall': {'support': 0.8872691933916423, 'agreement': 0.2553191489361702, 'direct_attack': 0.16393442622950818, 'undercutter_attack': 0.2, 'partial': 0.04819277108433735}, 'f1': {'support': 0.8281179138321995, 'agreement': 0.3342618384401114, 'direct_attack': 0.20512820512820515, 'undercutter_attack': 0.16564417177914112, 'partial': 0.06504065040650406}, 'support': {'support': 1029, 'agreement': 235, 'direct_attack': 122, 'undercutter_attack': 135, 'partial': 83}, 'micro_avg': {'precision': 0.6384039900249376, 'recall': 0.6384039900249376, 'f1': 0.6384039900249376, 'support': None}, 'macro_avg': {'precision': 0.35511307424877026, 'recall': 0.3109431079283316, 'f1': 0.3196385559172322, 'support': None}, 'weighted_avg': {'precision': 0.6068535564757539, 'recall': 0.6384039900249376, 'f1': 0.6131364361386061, 'support': None}}
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1583e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4411e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8214e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9778e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2916e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6277e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2433e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9840e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2797e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4702e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0769e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9063e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8790e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1111e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7741e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8477e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0112e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3845e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9779e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5548e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5217e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6539e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4239e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5410e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1190e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9194e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8002e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5318e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5429e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2594e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4489e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9325e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8244e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2168e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4280e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5296e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1495e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1269e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9434e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2885e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3038e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6016e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8305e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0122e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0806e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5195e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6024e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3985e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6600e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2653e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1614e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7045e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1008e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 17---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7805507745266781, 'agreement': 0.49504950495049505, 'direct_attack': 0.24175824175824176, 'undercutter_attack': 0.12980769230769232, 'partial': 0.09523809523809523}, 'recall': {'support': 0.882295719844358, 'agreement': 0.211864406779661, 'direct_attack': 0.18032786885245902, 'undercutter_attack': 0.2, 'partial': 0.04819277108433735}, 'f1': {'support': 0.828310502283105, 'agreement': 0.29673590504451036, 'direct_attack': 0.20657276995305165, 'undercutter_attack': 0.15743440233236153, 'partial': 0.064}, 'support': {'support': 1028, 'agreement': 236, 'direct_attack': 122, 'undercutter_attack': 135, 'partial': 83}, 'micro_avg': {'precision': 0.6296758104738155, 'recall': 0.6296758104738155, 'f1': 0.6296758104738155, 'support': None}, 'macro_avg': {'precision': 0.3484808617562405, 'recall': 0.304536153312163, 'f1': 0.31061071592260575, 'support': None}, 'weighted_avg': {'precision': 0.6073324097522119, 'recall': 0.6296758104738155, 'f1': 0.606795755727355, 'support': None}}
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1402e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0191e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0072e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9718e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9537e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1817e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9911e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8549e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8438e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6672e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6407e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4702e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8921e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6924e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5205e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1614e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7487e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4420e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1483e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1675e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8286e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2867e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1756e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3048e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8235e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7993e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5007e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5213e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4521e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7990e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3168e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4268e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4580e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2948e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6065e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3812e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2544e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3279e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0451e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6337e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5156e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3281e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2350e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0918e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4945e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8538e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3866e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2895e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6034e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6309e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0211e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5296e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9586e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3702e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6520e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5842e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3967e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0312e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 18---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7813036020583191, 'agreement': 0.5319148936170213, 'direct_attack': 0.22772277227722773, 'undercutter_attack': 0.12807881773399016, 'partial': 0.1}, 'recall': {'support': 0.8861867704280155, 'agreement': 0.211864406779661, 'direct_attack': 0.1885245901639344, 'undercutter_attack': 0.1925925925925926, 'partial': 0.04819277108433735}, 'f1': {'support': 0.8304466727438468, 'agreement': 0.30303030303030304, 'direct_attack': 0.20627802690582958, 'undercutter_attack': 0.15384615384615385, 'partial': 0.06504065040650406}, 'support': {'support': 1028, 'agreement': 236, 'direct_attack': 122, 'undercutter_attack': 135, 'partial': 83}, 'micro_avg': {'precision': 0.6321695760598504, 'recall': 0.6321695760598504, 'f1': 0.6321695760598504, 'support': None}, 'macro_avg': {'precision': 0.3538040171373117, 'recall': 0.30547222620970815, 'f1': 0.3117283613865275, 'support': None}, 'weighted_avg': {'precision': 0.612272341908653, 'recall': 0.6321695760598504, 'f1': 0.6088203585606656, 'support': None}}
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3954e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2807e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3372e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0475e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5569e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9546e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5249e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7992e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5479e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8892e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8922e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8587e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1019e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1545e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3594e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2029e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3058e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1575e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5001e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2359e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8850e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2592e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3028e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5571e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7639e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1766e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7164e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1202e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2381e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7790e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8305e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0152e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9162e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5620e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3531e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3691e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5189e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3130e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5123e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0738e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9739e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7053e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6991e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4833e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5922e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0675e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6710e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3198e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3249e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5660e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8859e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9292e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4783e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4462e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6912e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6802e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0493e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1835e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1332e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9393e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9848e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1626e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7315e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3766e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8333e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3245e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8214e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 19---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7815699658703071, 'agreement': 0.5390625, 'direct_attack': 0.2878787878787879, 'undercutter_attack': 0.14, 'partial': 0.10526315789473684}, 'recall': {'support': 0.8901846452866861, 'agreement': 0.2923728813559322, 'direct_attack': 0.1557377049180328, 'undercutter_attack': 0.2074074074074074, 'partial': 0.04878048780487805}, 'f1': {'support': 0.8323489323034984, 'agreement': 0.3791208791208791, 'direct_attack': 0.2021276595744681, 'undercutter_attack': 0.16716417910447762, 'partial': 0.06666666666666667}, 'support': {'support': 1029, 'agreement': 236, 'direct_attack': 122, 'undercutter_attack': 135, 'partial': 82}, 'micro_avg': {'precision': 0.6458852867830424, 'recall': 0.6458852867830424, 'f1': 0.6458852867830424, 'support': None}, 'macro_avg': {'precision': 0.3707548823287663, 'recall': 0.31889662535458735, 'f1': 0.329485663353998, 'support': None}, 'weighted_avg': {'precision': 0.6197674787712759, 'recall': 0.6458852867830424, 'f1': 0.6226016110515483, 'support': None}}
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9215e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3924e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9897e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3028e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2806e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3572e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3452e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9616e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3077e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3500e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0051e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2422e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7376e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1021e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4371e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0061e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7428e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0999e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5277e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0566e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6225e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2594e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2279e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3826e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5910e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6659e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8998e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0765e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2876e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4663e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8293e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5075e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4521e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8698e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7557e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7960e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7620e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2510e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4440e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3240e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9910e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7135e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2246e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1048e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1856e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3009e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6710e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1504e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3744e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9482e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5549e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4643e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3077e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0980e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2077e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2259e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8033e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5804e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2150e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5540e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2129e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4971e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2604e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6839e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5780e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5428e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4854e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3773e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1299e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7862e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9686e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7575e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9878e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5490e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4943e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8991e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2110e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7923e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2715e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 20---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7758913412563667, 'agreement': 0.5441176470588235, 'direct_attack': 0.2524271844660194, 'undercutter_attack': 0.125, 'partial': 0.1282051282051282}, 'recall': {'support': 0.8882410106899903, 'agreement': 0.15677966101694915, 'direct_attack': 0.21311475409836064, 'undercutter_attack': 0.20149253731343283, 'partial': 0.060240963855421686}, 'f1': {'support': 0.8282736746714998, 'agreement': 0.24342105263157895, 'direct_attack': 0.2311111111111111, 'undercutter_attack': 0.15428571428571428, 'partial': 0.0819672131147541}, 'support': {'support': 1029, 'agreement': 236, 'direct_attack': 122, 'undercutter_attack': 134, 'partial': 83}, 'micro_avg': {'precision': 0.6290523690773068, 'recall': 0.6290523690773068, 'f1': 0.6290523690773068, 'support': None}, 'macro_avg': {'precision': 0.3651282601972675, 'recall': 0.30397378539483094, 'f1': 0.3078117531629317, 'support': None}, 'weighted_avg': {'precision': 0.6140842250651893, 'recall': 0.6290523690773068, 'f1': 0.6018791144740597, 'support': None}}
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6043e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6258e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2231e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2797e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3552e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0960e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5722e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1874e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4508e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5296e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0374e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5722e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1665e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3089e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9343e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8937e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1130e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2725e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2714e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1450e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1895e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9443e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0697e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1240e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0375e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7194e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5701e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3673e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2988e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2131e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7446e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5831e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0303e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3702e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1181e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5105e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8903, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7618e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7518e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4733e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2301e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6954e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7674e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4339e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5480e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7112e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1491e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9837e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0566e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1958e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9031e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7851e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2735e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8423e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6316e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3933e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1756e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6066e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2281e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6225e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0878e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6385e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3118e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2644e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5429e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0080e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0300e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5580e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8574e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7142e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7941e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2450e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4802e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2147e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4541e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9625e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1706e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0224e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5641e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4279e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5032e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7094e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0149e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2662e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6105e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7484e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0435e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9355e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9687e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3630e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6870e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7385e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2199e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5107e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7851e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8375e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)


		-------------RUN 4-----------
			------------EPOCH 1---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6166419019316494, 'agreement': 0.0, 'direct_attack': 0.11436541143654114, 'undercutter_attack': 0.0, 'partial': 0.0}, 'recall': {'support': 0.50920245398773, 'agreement': 0.0, 'direct_attack': 0.6212121212121212, 'undercutter_attack': 0.0, 'partial': 0.0}, 'f1': {'support': 0.5577956989247311, 'agreement': 0.0, 'direct_attack': 0.19316843345111895, 'undercutter_attack': 0.0, 'partial': 0.0}, 'support': {'support': 815, 'agreement': 187, 'direct_attack': 132, 'undercutter_attack': 145, 'partial': 111}, 'micro_avg': {'precision': 0.3575539568345324, 'recall': 0.3575539568345324, 'f1': 0.3575539568345324, 'support': None}, 'macro_avg': {'precision': 0.1462014626736381, 'recall': 0.22608291503997027, 'f1': 0.15019282647517002, 'support': None}, 'weighted_avg': {'precision': 0.3724168232977825, 'recall': 0.35755395683453234, 'f1': 0.34539692650302417, 'support': None}}
Loss: tensor(2.4881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6852, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9843, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3660, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6769, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3955, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7844, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7714, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5652, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0671, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6998, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2601, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4680, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4806, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6693, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7753, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6635, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2785, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3560, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1750, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6427, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5862, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5947, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2904, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1885, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6683, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2985, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9994, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2794, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1662, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8971, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9871, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3813, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9739, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0862, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5873, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6885, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6997, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7744, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9871, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9720, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8947, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8929, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6927, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2791, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5705, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7962, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7852, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8754, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2641, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3713, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5926, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6785, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1817, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8985, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6774, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6955, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2873, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4785, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4635, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1852, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9794, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5652, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5987, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4940, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4693, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4652, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0935, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6977, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5761, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2994, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3847, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3868, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5926, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4785, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7652, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9831, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4847, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3680, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3626, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 2---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6318681318681318, 'agreement': 0.39015151515151514, 'direct_attack': 0.0, 'undercutter_attack': 0.058823529411764705, 'partial': 0.0}, 'recall': {'support': 0.8466257668711656, 'agreement': 0.5508021390374331, 'direct_attack': 0.0, 'undercutter_attack': 0.013793103448275862, 'partial': 0.0}, 'f1': {'support': 0.7236497115888831, 'agreement': 0.45676274944567624, 'direct_attack': 0.0, 'undercutter_attack': 0.0223463687150838, 'partial': 0.0}, 'support': {'support': 815, 'agreement': 187, 'direct_attack': 132, 'undercutter_attack': 145, 'partial': 111}, 'micro_avg': {'precision': 0.5719424460431655, 'recall': 0.5719424460431655, 'f1': 0.5719424460431655, 'support': None}, 'macro_avg': {'precision': 0.21616863528628233, 'recall': 0.28224420187137494, 'f1': 0.24055176594992864, 'support': None}, 'weighted_avg': {'precision': 0.42910810976299757, 'recall': 0.5719424460431655, 'f1': 0.48807868529134407, 'support': None}}
Loss: tensor(6.1624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1798, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6947, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1840, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4801, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3916, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1922, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4840, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2921, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4604, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5632, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2847, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4694, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0957, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1626, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3926, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2873, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4751, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6971, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2683, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5871, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5660, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3906, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5560, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2885, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7738, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6481, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8987, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6998, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6847, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6913, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8922, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9947, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5720, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4978, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6757, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6798, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1926, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2898, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3847, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4777, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9871, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1757, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4794, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3796, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6719, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6813, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1826, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0831, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7796, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6693, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2885, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3998, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8922, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9694, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6847, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4962, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3801, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0740, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3929, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9654, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3972, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2569, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5132, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 3---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.710727969348659, 'agreement': 0.42168674698795183, 'direct_attack': 0.12669683257918551, 'undercutter_attack': 0.07894736842105263, 'partial': 0.0}, 'recall': {'support': 0.45465686274509803, 'agreement': 0.3763440860215054, 'direct_attack': 0.6363636363636364, 'undercutter_attack': 0.020689655172413793, 'partial': 0.0}, 'f1': {'support': 0.554559043348281, 'agreement': 0.39772727272727276, 'direct_attack': 0.2113207547169811, 'undercutter_attack': 0.032786885245901634, 'partial': 0.0}, 'support': {'support': 816, 'agreement': 186, 'direct_attack': 132, 'undercutter_attack': 145, 'partial': 111}, 'micro_avg': {'precision': 0.37985611510791367, 'recall': 0.37985611510791367, 'f1': 0.37985611510791367, 'support': None}, 'macro_avg': {'precision': 0.2676117834673698, 'recall': 0.29761084806053073, 'f1': 0.2392787912076873, 'support': None}, 'weighted_avg': {'precision': 0.4939274160070286, 'recall': 0.37985611510791367, 'f1': 0.4022632302753721, 'support': None}}
Loss: tensor(1.0294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7860, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4813, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3553, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1777, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5915, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3635, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4569, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2938, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2694, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8777, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1604, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3797, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2913, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1757, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7765, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5374, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1797, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3900, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1769, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1569, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1927, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3738, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6844, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3613, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5662, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1694, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0874, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5983, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6785, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9956, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8906, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2826, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0801, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0652, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4374, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5915, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1972, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0560, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0935, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5862, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2796, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7904, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5873, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5720, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5761, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1912, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7994, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5997, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8978, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2374, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7765, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6880, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0662, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3754, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4801, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0660, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6719, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0794, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0714, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1801, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0694, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0569, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2569, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2632, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0913, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2794, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9978, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4921, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0922, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0947, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0635, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6890, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0957, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4926, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2560, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5798, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7719, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6978, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3511, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8635, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8880, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1994, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5754, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2874, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0683, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7738, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9936, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3087, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 4---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6982892690513219, 'agreement': 0.3937007874015748, 'direct_attack': 0.14864864864864866, 'undercutter_attack': 0.06578947368421052, 'partial': 0.1198501872659176}, 'recall': {'support': 0.5502450980392157, 'agreement': 0.5347593582887701, 'direct_attack': 0.08333333333333333, 'undercutter_attack': 0.06944444444444445, 'partial': 0.2882882882882883}, 'f1': {'support': 0.6154900616860863, 'agreement': 0.45351473922902497, 'direct_attack': 0.10679611650485436, 'undercutter_attack': 0.06756756756756756, 'partial': 0.1693121693121693}, 'support': {'support': 816, 'agreement': 187, 'direct_attack': 132, 'undercutter_attack': 144, 'partial': 111}, 'micro_avg': {'precision': 0.4330935251798561, 'recall': 0.4330935251798561, 'f1': 0.4330935251798561, 'support': None}, 'macro_avg': {'precision': 0.28525567321033474, 'recall': 0.3052141044788103, 'f1': 0.28253613085994045, 'support': None}, 'weighted_avg': {'precision': 0.4933991132436245, 'recall': 0.4330935251798561, 'f1': 0.4529982837940255, 'support': None}}
Loss: tensor(1.8703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0683, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0826, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4777, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0907, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0840, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6940, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8604, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0791, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0427, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4705, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0616, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0660, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0903, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6972, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9794, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0783, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6427, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8940, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8785, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0977, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1801, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1962, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0481, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8284, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0635, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7794, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0806, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0955, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3915, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0797, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0757, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1654, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1751, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0796, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5983, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0915, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0750, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4777, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1742, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4813, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1719, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0374, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7927, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8720, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1867, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0481, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0616, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0291, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 5---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6564003849855631, 'agreement': 0.44370860927152317, 'direct_attack': 0.125, 'undercutter_attack': 0.0, 'partial': 0.25925925925925924}, 'recall': {'support': 0.8368098159509203, 'agreement': 0.3582887700534759, 'direct_attack': 0.1590909090909091, 'undercutter_attack': 0.0, 'partial': 0.06306306306306306}, 'f1': {'support': 0.7357065803667745, 'agreement': 0.39644970414201186, 'direct_attack': 0.14, 'undercutter_attack': 0.0, 'partial': 0.10144927536231885}, 'support': {'support': 815, 'agreement': 187, 'direct_attack': 132, 'undercutter_attack': 145, 'partial': 111}, 'micro_avg': {'precision': 0.5589928057553957, 'recall': 0.5589928057553957, 'f1': 0.5589928057553957, 'support': None}, 'macro_avg': {'precision': 0.2968736507032691, 'recall': 0.28345051163167373, 'f1': 0.2747211119742211, 'support': None}, 'weighted_avg': {'precision': 0.4771349650897745, 'recall': 0.5589928057553957, 'f1': 0.5060991562868309, 'support': None}}
Loss: tensor(0.4352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9751, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0994, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2977, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3784, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0720, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0694, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0837, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0831, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0977, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2817, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2957, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0451, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1720, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0750, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0784, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0604, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0701, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0553, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1677, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0713, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1601, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0652, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1553, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5765, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0817, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0754, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4750, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0798, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0635, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0955, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5427, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0240, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 6---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6736621196222455, 'agreement': 0.38317757009345793, 'direct_attack': 0.1423728813559322, 'undercutter_attack': 0.09090909090909091, 'partial': 0.46153846153846156}, 'recall': {'support': 0.7877300613496933, 'agreement': 0.2192513368983957, 'direct_attack': 0.3181818181818182, 'undercutter_attack': 0.013793103448275862, 'partial': 0.05405405405405406}, 'f1': {'support': 0.7262443438914027, 'agreement': 0.27891156462585037, 'direct_attack': 0.19672131147540983, 'undercutter_attack': 0.023952095808383235, 'partial': 0.0967741935483871}, 'support': {'support': 815, 'agreement': 187, 'direct_attack': 132, 'undercutter_attack': 145, 'partial': 111}, 'micro_avg': {'precision': 0.5273381294964029, 'recall': 0.5273381294964029, 'f1': 0.5273381294964029, 'support': None}, 'macro_avg': {'precision': 0.3503320247038376, 'recall': 0.2786020747864474, 'f1': 0.26452070186988663, 'support': None}, 'weighted_avg': {'precision': 0.5063990221950915, 'recall': 0.5273381294964029, 'f1': 0.4922502196743654, 'support': None}}
Loss: tensor(0.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0553, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0997, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0757, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2680, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1427, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3929, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7427, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 7---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6866002214839424, 'agreement': 0.35294117647058826, 'direct_attack': 0.23809523809523808, 'undercutter_attack': 0.11904761904761904, 'partial': 0.4375}, 'recall': {'support': 0.7598039215686274, 'agreement': 0.0962566844919786, 'direct_attack': 0.15267175572519084, 'undercutter_attack': 0.27586206896551724, 'partial': 0.06306306306306306}, 'f1': {'support': 0.7213496218731821, 'agreement': 0.15126050420168066, 'direct_attack': 0.18604651162790697, 'undercutter_attack': 0.16632016632016627, 'partial': 0.11023622047244093}, 'support': {'support': 816, 'agreement': 187, 'direct_attack': 131, 'undercutter_attack': 145, 'partial': 111}, 'micro_avg': {'precision': 0.5071942446043165, 'recall': 0.5071942446043165, 'f1': 0.5071942446043165, 'support': None}, 'macro_avg': {'precision': 0.3668368510194776, 'recall': 0.2695314987628754, 'f1': 0.2670426048990754, 'support': None}, 'weighted_avg': {'precision': 0.5203457997721423, 'recall': 0.5071942446043165, 'f1': 0.4875048513283106, 'support': None}}
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0919, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0429, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3987, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7601, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 8---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6859592711682744, 'agreement': 0.43333333333333335, 'direct_attack': 0.20353982300884957, 'undercutter_attack': 0.14457831325301204, 'partial': 0.25}, 'recall': {'support': 0.7852760736196319, 'agreement': 0.34759358288770054, 'direct_attack': 0.17424242424242425, 'undercutter_attack': 0.16551724137931034, 'partial': 0.06306306306306306}, 'f1': {'support': 0.7322654462242564, 'agreement': 0.3857566765578635, 'direct_attack': 0.18775510204081633, 'undercutter_attack': 0.15434083601286172, 'partial': 0.10071942446043164}, 'support': {'support': 815, 'agreement': 187, 'direct_attack': 132, 'undercutter_attack': 145, 'partial': 111}, 'micro_avg': {'precision': 0.5460431654676259, 'recall': 0.5460431654676259, 'f1': 0.5460431654676259, 'support': None}, 'macro_avg': {'precision': 0.34348214815269384, 'recall': 0.307138477038426, 'f1': 0.31216749705924596, 'support': None}, 'weighted_avg': {'precision': 0.5148714038808142, 'recall': 0.5460431654676259, 'f1': 0.5232199913636331, 'support': None}}
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 9---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6839481555333998, 'agreement': 0.4796747967479675, 'direct_attack': 0.21052631578947367, 'undercutter_attack': 0.14285714285714285, 'partial': 0.3181818181818182}, 'recall': {'support': 0.8406862745098039, 'agreement': 0.3155080213903743, 'direct_attack': 0.15151515151515152, 'undercutter_attack': 0.14583333333333334, 'partial': 0.06306306306306306}, 'f1': {'support': 0.7542605827377681, 'agreement': 0.38064516129032255, 'direct_attack': 0.1762114537444934, 'undercutter_attack': 0.1443298969072165, 'partial': 0.10526315789473685}, 'support': {'support': 816, 'agreement': 187, 'direct_attack': 132, 'undercutter_attack': 144, 'partial': 111}, 'micro_avg': {'precision': 0.5705035971223021, 'recall': 0.5705035971223021, 'f1': 0.5705035971223021, 'support': None}, 'macro_avg': {'precision': 0.36703764582196036, 'recall': 0.3033211687623453, 'f1': 0.31214205051490745, 'support': None}, 'weighted_avg': {'precision': 0.5262445798424066, 'recall': 0.5705035971223021, 'f1': 0.5340898620507463, 'support': None}}
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9880, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4118e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 10---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7001127395715896, 'agreement': 0.39267015706806285, 'direct_attack': 0.13548387096774195, 'undercutter_attack': 0.10526315789473684, 'partial': 0.2916666666666667}, 'recall': {'support': 0.7619631901840491, 'agreement': 0.40106951871657753, 'direct_attack': 0.1590909090909091, 'undercutter_attack': 0.09655172413793103, 'partial': 0.06306306306306306}, 'f1': {'support': 0.7297297297297298, 'agreement': 0.3968253968253968, 'direct_attack': 0.14634146341463417, 'undercutter_attack': 0.10071942446043165, 'partial': 0.1037037037037037}, 'support': {'support': 815, 'agreement': 187, 'direct_attack': 132, 'undercutter_attack': 145, 'partial': 111}, 'micro_avg': {'precision': 0.5309352517985612, 'recall': 0.5309352517985612, 'f1': 0.5309352517985612, 'support': None}, 'macro_avg': {'precision': 0.3250393184337596, 'recall': 0.296347681038506, 'f1': 0.29546394362677925, 'support': None}, 'weighted_avg': {'precision': 0.510462756104354, 'recall': 0.5309352517985612, 'f1': 0.5139342300465355, 'support': None}}
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8589e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 11---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6925498426023085, 'agreement': 0.40588235294117647, 'direct_attack': 0.16666666666666666, 'undercutter_attack': 0.11764705882352941, 'partial': 0.3181818181818182}, 'recall': {'support': 0.8098159509202454, 'agreement': 0.3689839572192513, 'direct_attack': 0.1590909090909091, 'undercutter_attack': 0.09655172413793103, 'partial': 0.06306306306306306}, 'f1': {'support': 0.7466063348416289, 'agreement': 0.38655462184873945, 'direct_attack': 0.1627906976744186, 'undercutter_attack': 0.10606060606060606, 'partial': 0.10526315789473685}, 'support': {'support': 815, 'agreement': 187, 'direct_attack': 132, 'undercutter_attack': 145, 'partial': 111}, 'micro_avg': {'precision': 0.5546762589928057, 'recall': 0.5546762589928057, 'f1': 0.5546762589928057, 'support': None}, 'macro_avg': {'precision': 0.34018554784309984, 'recall': 0.29950112088628, 'f1': 0.301455083664026, 'support': None}, 'weighted_avg': {'precision': 0.5141763504089747, 'recall': 0.5546762589928057, 'f1': 0.5246915450933588, 'support': None}}
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4854e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3179e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8578e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5521e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2585e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7801e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6580e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6187e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5825e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 12---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6942328618063112, 'agreement': 0.39655172413793105, 'direct_attack': 0.1796875, 'undercutter_attack': 0.11643835616438356, 'partial': 0.30434782608695654}, 'recall': {'support': 0.7828220858895706, 'agreement': 0.3689839572192513, 'direct_attack': 0.17424242424242425, 'undercutter_attack': 0.11724137931034483, 'partial': 0.06306306306306306}, 'f1': {'support': 0.7358708189158016, 'agreement': 0.38227146814404434, 'direct_attack': 0.17692307692307693, 'undercutter_attack': 0.11683848797250859, 'partial': 0.10447761194029849}, 'support': {'support': 815, 'agreement': 187, 'direct_attack': 132, 'undercutter_attack': 145, 'partial': 111}, 'micro_avg': {'precision': 0.5424460431654676, 'recall': 0.5424460431654676, 'f1': 0.5424460431654676, 'support': None}, 'macro_avg': {'precision': 0.33825165363911647, 'recall': 0.30127058194493084, 'f1': 0.30327629277914603, 'support': None}, 'weighted_avg': {'precision': 0.513913579226924, 'recall': 0.5424460431654676, 'f1': 0.5202244056075883, 'support': None}}
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5047e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3160e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5037e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2413e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1586e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0868, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4794e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5471e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5166e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5976e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1857e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4169e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2351e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0091e-05, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 13---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6898002103049422, 'agreement': 0.4236111111111111, 'direct_attack': 0.15492957746478872, 'undercutter_attack': 0.10606060606060606, 'partial': 0.3333333333333333}, 'recall': {'support': 0.8049079754601227, 'agreement': 0.32620320855614976, 'direct_attack': 0.16666666666666666, 'undercutter_attack': 0.09655172413793103, 'partial': 0.06306306306306306}, 'f1': {'support': 0.7429218573046433, 'agreement': 0.36858006042296076, 'direct_attack': 0.16058394160583941, 'undercutter_attack': 0.10108303249097474, 'partial': 0.10606060606060606}, 'support': {'support': 815, 'agreement': 187, 'direct_attack': 132, 'undercutter_attack': 145, 'partial': 111}, 'micro_avg': {'precision': 0.5467625899280576, 'recall': 0.5467625899280576, 'f1': 0.5467625899280576, 'support': None}, 'macro_avg': {'precision': 0.34154696765495624, 'recall': 0.29147852757678666, 'f1': 0.2958458995770049, 'support': None}, 'weighted_avg': {'precision': 0.5138359289787379, 'recall': 0.5467625899280576, 'f1': 0.5194479368908398, 'support': None}}
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7024e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5259e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6823e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9436e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3806e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8619e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1199e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3735e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0070e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1232e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4663e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1737e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7439e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9305e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1039e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1768e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4420e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8337e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8004e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7013e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1898e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8032e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2937e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0769e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5863e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9626e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5955e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5249e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1798e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6823e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5924e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 14---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.696969696969697, 'agreement': 0.3838383838383838, 'direct_attack': 0.1875, 'undercutter_attack': 0.12666666666666668, 'partial': 0.22727272727272727}, 'recall': {'support': 0.7892156862745098, 'agreement': 0.40860215053763443, 'direct_attack': 0.13636363636363635, 'undercutter_attack': 0.1310344827586207, 'partial': 0.04504504504504504}, 'f1': {'support': 0.7402298850574713, 'agreement': 0.3958333333333333, 'direct_attack': 0.15789473684210525, 'undercutter_attack': 0.12881355932203392, 'partial': 0.07518796992481203}, 'support': {'support': 816, 'agreement': 186, 'direct_attack': 132, 'undercutter_attack': 145, 'partial': 111}, 'micro_avg': {'precision': 0.5482014388489208, 'recall': 0.5482014388489208, 'f1': 0.5482014388489208, 'support': None}, 'macro_avg': {'precision': 0.324449494949495, 'recall': 0.30205220019588924, 'f1': 0.2995918968959511, 'support': None}, 'weighted_avg': {'precision': 0.5096871593634184, 'recall': 0.5482014388489208, 'f1': 0.5219557713909377, 'support': None}}
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7215e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9043e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8366e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5541e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8407e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0654e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5347e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6398e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0414e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7559e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8831e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9113e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9738e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8972e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6801, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6085e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0091e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7327e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0011e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8921e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1169e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0768e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5238e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0788e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3796e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9505e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3361e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5299e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8406e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6811e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8700e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9618e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2735e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1514e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9304e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2816e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0929e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3321e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1959e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7741e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7550e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3765e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8034e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0476e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3624e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0434e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4129e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1644e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8789e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7186e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9516e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 15---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6945031712473573, 'agreement': 0.4217687074829932, 'direct_attack': 0.16923076923076924, 'undercutter_attack': 0.10416666666666667, 'partial': 0.34782608695652173}, 'recall': {'support': 0.8051470588235294, 'agreement': 0.3315508021390374, 'direct_attack': 0.16666666666666666, 'undercutter_attack': 0.10416666666666667, 'partial': 0.07207207207207207}, 'f1': {'support': 0.7457434733257662, 'agreement': 0.37125748502994016, 'direct_attack': 0.16793893129770993, 'undercutter_attack': 0.10416666666666667, 'partial': 0.11940298507462686}, 'support': {'support': 816, 'agreement': 187, 'direct_attack': 132, 'undercutter_attack': 144, 'partial': 111}, 'micro_avg': {'precision': 0.5496402877697841, 'recall': 0.5496402877697841, 'f1': 0.5496402877697841, 'support': None}, 'macro_avg': {'precision': 0.34749908031686166, 'recall': 0.29592065327359446, 'f1': 0.30170190827894194, 'support': None}, 'weighted_avg': {'precision': 0.5190881246243156, 'recall': 0.5496402877697841, 'f1': 0.5240097080640326, 'support': None}}
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2403e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5491e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7721e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6095e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1916e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0436e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4378e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3684e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8225e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9325e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9073e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1556e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3179e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0415e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1798e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3321e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8579e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9203e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6368e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0753, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3190e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2047e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3896e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5026e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0363e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6982e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9495e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7516e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9243e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4430e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6158e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4854e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9730e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9276e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2585e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5973e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7094e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1230e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8589e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2856e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9164e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2441e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6188e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5359e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1372e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7651e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2462e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6507e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8808e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9749e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9939e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5348e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8065e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2534e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4230e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1475e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6106e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0585e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 16---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6934306569343066, 'agreement': 0.42073170731707316, 'direct_attack': 0.1834862385321101, 'undercutter_attack': 0.11764705882352941, 'partial': 0.2727272727272727}, 'recall': {'support': 0.8159509202453987, 'agreement': 0.3689839572192513, 'direct_attack': 0.15151515151515152, 'undercutter_attack': 0.1103448275862069, 'partial': 0.05405405405405406}, 'f1': {'support': 0.7497181510710259, 'agreement': 0.3931623931623931, 'direct_attack': 0.16597510373443985, 'undercutter_attack': 0.11387900355871886, 'partial': 0.09022556390977444}, 'support': {'support': 815, 'agreement': 187, 'direct_attack': 132, 'undercutter_attack': 145, 'partial': 111}, 'micro_avg': {'precision': 0.5582733812949641, 'recall': 0.5582733812949641, 'f1': 0.5582733812949641, 'support': None}, 'macro_avg': {'precision': 0.3376045868668584, 'recall': 0.30016978212401246, 'f1': 0.3025920430872705, 'support': None}, 'weighted_avg': {'precision': 0.514657948890741, 'recall': 0.5582733812949641, 'f1': 0.527322206796546, 'support': None}}
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2289e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7960e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7518e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2170e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6537e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8650e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7982e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2180e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3925e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3866e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5600e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9586e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4977e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0352e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8558e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1644e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7235e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9405e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7851e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4905e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6297e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3745e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6036e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6085e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1999e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8165e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6025e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7217e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2231e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9155e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9233e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7681e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0939e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7467e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9485e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4266e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9404e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8868e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4027e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2119e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7357e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5773e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5307e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7952e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8790e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6882e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7227e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7043e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7811e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2592e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4448e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6701e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0869e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4784e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9113e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7667e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9616e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8707e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5824e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8285e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0314e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5347e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4320e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0525e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2897e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1099e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3342e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9265e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4954e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6801e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8181e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9546e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1502e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6455e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4844e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6255e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6248e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7760e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6740e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4248e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1000e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2995e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5174e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9628e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 17---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6973821989528796, 'agreement': 0.4222222222222222, 'direct_attack': 0.18620689655172415, 'undercutter_attack': 0.11278195488721804, 'partial': 0.36363636363636365}, 'recall': {'support': 0.8161764705882353, 'agreement': 0.3048128342245989, 'direct_attack': 0.20454545454545456, 'undercutter_attack': 0.10416666666666667, 'partial': 0.07207207207207207}, 'f1': {'support': 0.7521174477696217, 'agreement': 0.35403726708074534, 'direct_attack': 0.19494584837545126, 'undercutter_attack': 0.10830324909747291, 'partial': 0.12030075187969926}, 'support': {'support': 816, 'agreement': 187, 'direct_attack': 132, 'undercutter_attack': 144, 'partial': 111}, 'micro_avg': {'precision': 0.556115107913669, 'recall': 0.556115107913669, 'f1': 0.556115107913669, 'support': None}, 'macro_avg': {'precision': 0.3564459272500815, 'recall': 0.30035469961940553, 'f1': 0.3059409128405981, 'support': None}, 'weighted_avg': {'precision': 0.5246064590743371, 'recall': 0.556115107913669, 'f1': 0.5284997911067288, 'support': None}}
Loss: tensor(8.3533e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5158e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2343e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8698e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4047e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9464e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9306e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9416e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2583e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4905e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9204e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9940e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4018e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3795e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6016e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5077e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1988e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8891e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9991e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7418e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9285e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0353e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5612e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7822e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9272e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8387e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7608e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0866e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7769e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4976e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5128e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6903e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9576e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6993e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0403e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3033e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3743e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3733e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9406e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4320e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1645e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1190e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5298e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3431e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0424e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2555e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9548e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8211e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9525e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1190e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6651e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0920e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6367e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5713e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5871e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2451e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1926e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0918e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6963e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9668e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3796e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2252e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2825e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9083e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3016e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4551e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7881e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5066e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6024e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2765e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9928e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6076e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1585e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6376e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5742e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0797e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8505e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1744e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2522e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3924e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8699e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9555e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9639e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9898e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1645e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3887e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6537e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8667e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4892e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6428e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3673e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7365e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6983e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8335e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8241e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3167e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7666e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0738e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7478e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8475e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 18---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6971307120085016, 'agreement': 0.42073170731707316, 'direct_attack': 0.1724137931034483, 'undercutter_attack': 0.13513513513513514, 'partial': 0.2857142857142857}, 'recall': {'support': 0.803921568627451, 'agreement': 0.3689839572192513, 'direct_attack': 0.15151515151515152, 'undercutter_attack': 0.1388888888888889, 'partial': 0.05405405405405406}, 'f1': {'support': 0.7467273762094478, 'agreement': 0.3931623931623931, 'direct_attack': 0.16129032258064518, 'undercutter_attack': 0.136986301369863, 'partial': 0.09090909090909091}, 'support': {'support': 816, 'agreement': 187, 'direct_attack': 132, 'undercutter_attack': 144, 'partial': 111}, 'micro_avg': {'precision': 0.5546762589928057, 'recall': 0.5546762589928057, 'f1': 0.5546762589928057, 'support': None}, 'macro_avg': {'precision': 0.34222512665568877, 'recall': 0.3034727240609594, 'f1': 0.305815096846288, 'support': None}, 'weighted_avg': {'precision': 0.5190416231155613, 'recall': 0.5546762589928057, 'f1': 0.5280274572497061, 'support': None}}
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7609e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6446e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5489e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8426e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2252e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1883e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4015e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4693e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2038e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7035e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1775e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6196e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8306e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1838e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4905e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9425e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7741e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7861e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9059e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3190e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8860e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8154e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8547e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7900e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3158e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7990e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5862e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2622e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8293e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1402e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8244e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1696e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9334e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9515e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8093e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6800e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9940e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1474e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2653e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6709e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3319e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1777e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7075e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0191e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3470e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1342e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8544e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8920e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6248e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5722e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9422e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6528e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7983e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3936e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8174e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8559e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6316e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9253e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9060e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5892e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5631e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9798e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1917e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5177e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2222e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6772e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5077e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4875e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1520e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5813e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3743e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8596e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5105e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1825e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1986e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7605e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7123e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2622e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2017e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3652e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1321e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1208e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3310e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7630e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0412e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6930e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8181e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2895e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6994e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7870e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3873e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8659e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8525e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8726e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3935, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6793e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3743e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2583e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7869e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6185e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5056e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4671e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0576e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6963e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5268e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1321e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4845e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2280e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8375e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6397e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5491e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2068e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5592e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3796e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3581e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7557e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6416e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1565e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3391e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7741e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5289e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6731e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0424e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5279e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1635e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7892e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3866e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4351e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9334e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4076e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6319e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0554e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1414e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4157e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0797, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3297e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 19---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6982942430703625, 'agreement': 0.42857142857142855, 'direct_attack': 0.17006802721088435, 'undercutter_attack': 0.125, 'partial': 0.38095238095238093}, 'recall': {'support': 0.803680981595092, 'agreement': 0.32085561497326204, 'direct_attack': 0.1893939393939394, 'undercutter_attack': 0.12413793103448276, 'partial': 0.07207207207207207}, 'f1': {'support': 0.7472903593839133, 'agreement': 0.3669724770642202, 'direct_attack': 0.17921146953405018, 'undercutter_attack': 0.1245674740484429, 'partial': 0.1212121212121212}, 'support': {'support': 815, 'agreement': 187, 'direct_attack': 132, 'undercutter_attack': 145, 'partial': 111}, 'micro_avg': {'precision': 0.5510791366906475, 'recall': 0.5510791366906475, 'f1': 0.5510791366906475, 'support': None}, 'macro_avg': {'precision': 0.3605772159610113, 'recall': 0.30202810781376965, 'f1': 0.3078507802485495, 'support': None}, 'weighted_avg': {'precision': 0.5266995389372328, 'recall': 0.5510791366906475, 'f1': 0.5272217548769517, 'support': None}}
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5901e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3490e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4539e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9354e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0827e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4378e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5852e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5205e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8557e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4672e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3512e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0696e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6043e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6255e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1999e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4702e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5680e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0536e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4924e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2039e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2298e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9858e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4521e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0061e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9455e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4098e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3016e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4450e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6317e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5659e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0239e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1434e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6709e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9485e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3673e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5915e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9505e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7639e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8717e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7273e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0132e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2522e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3721e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4814e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7811e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9830e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7548e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1756e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0957e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8193e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9728e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2825e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4348e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8114e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3963e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8535e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9798e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2794e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4620e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3601e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0455e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1674e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1928e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5983e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7497e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1543e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1974e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8596e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4066e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6619e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5941e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5440e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2532e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1160e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5761e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0151e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0503e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8275e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1866e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7245e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3924e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5167e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3215e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2752e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3327e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4159e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8314e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7497e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8699e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7861e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7347e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5016e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3523e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7878e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1896e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7384e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0858e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5066e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3191e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1502e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2007e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9919e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3388e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7427e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0191e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5066e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8063e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8316e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1814e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6779e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0908e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7324e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6903e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2857e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3673e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3957e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4511e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8649e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1756e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3116e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3449e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2392e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7448e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6217e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2201e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3611e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8194e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8707e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9867e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4914e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0291e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7113e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0181e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7550e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3157e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2895e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4711e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5107e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0322e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4499e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2552e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9578e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5852e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2298e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6557e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3167e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8367e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0282e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4986e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9028e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9223e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8174e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5477e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4016e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2482e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7628e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4199e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 20---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6966773847802786, 'agreement': 0.4129032258064516, 'direct_attack': 0.18181818181818182, 'undercutter_attack': 0.11875, 'partial': 0.2857142857142857}, 'recall': {'support': 0.7975460122699386, 'agreement': 0.3422459893048128, 'direct_attack': 0.16666666666666666, 'undercutter_attack': 0.1310344827586207, 'partial': 0.05405405405405406}, 'f1': {'support': 0.7437070938215102, 'agreement': 0.3742690058479532, 'direct_attack': 0.17391304347826086, 'undercutter_attack': 0.12459016393442623, 'partial': 0.09090909090909091}, 'support': {'support': 815, 'agreement': 187, 'direct_attack': 132, 'undercutter_attack': 145, 'partial': 111}, 'micro_avg': {'precision': 0.5474820143884892, 'recall': 0.5474820143884892, 'f1': 0.5474820143884892, 'support': None}, 'macro_avg': {'precision': 0.3391726156238396, 'recall': 0.2983094410108186, 'f1': 0.3014776795982482, 'support': None}, 'weighted_avg': {'precision': 0.5165021636949778, 'recall': 0.5474820143884892, 'f1': 0.5231817195385824, 'support': None}}
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3176e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6234e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2362e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6567e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8020e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8586e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4971e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1756e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6001e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4601e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1283e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3578e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4613e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2692e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1826e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5568e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0874, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4693e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1846e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2441e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4569e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1623e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9688e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9194e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4729e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7847e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7872e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9821e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4257e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7073e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9141e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2168e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0364e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7497e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3609e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6619e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1855e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2341e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3593e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8486e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8435e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8184e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7073e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2259e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0310e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6894e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7103e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1028e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4067e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4047e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2108e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7811e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1977e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9767e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2168e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5560e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0040e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1159e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3664e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6924e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9716e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8807e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6489e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5126e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8435e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5580e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3402e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4671e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4327e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8535e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5017e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8998e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8587e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1511e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3540e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3430e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4521e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8928e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2359e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9082e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8544e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2622e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6839e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4793e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3179e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6325e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8840e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0182e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3037e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9059e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4775e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8184e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2046e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0763e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6727e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8980e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7608e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9967e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4590e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4158e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3067e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1926e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2571e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0218e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9443e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7345e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1645e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1965e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9491e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7981e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3836e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6125e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5741e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3945e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5277e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4409e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6116e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7575e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2925e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2443e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7657e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1005e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5486e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7124e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8877e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1645e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3310e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2017e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0633e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1442e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0109e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8335e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5207e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1807e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4517e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6567e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9838e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1723e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7578e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2888e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0939e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0716e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7881e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2804e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5236e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1238e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1714e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7085e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5782e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5468e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7467e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6470e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8667e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7152e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8275e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6286e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7215e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3712e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4681e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0907e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2259e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7142e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5338e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2433e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1048e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0170e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6721e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3821e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8011e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5062e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5268e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7255e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0172e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4823e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4772e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0626e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5762e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1874e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4035e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0149e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9149e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7669e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8345e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)


		-------------RUN 5-----------
			------------EPOCH 1---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.0, 'agreement': 0.0, 'direct_attack': 0.11788617886178862, 'undercutter_attack': 0.10630841121495327, 'partial': 0.0}, 'recall': {'support': 0.0, 'agreement': 0.0, 'direct_attack': 0.38666666666666666, 'undercutter_attack': 0.6642335766423357, 'partial': 0.0}, 'f1': {'support': 0.0, 'agreement': 0.0, 'direct_attack': 0.18068535825545173, 'undercutter_attack': 0.18328298086606243, 'partial': 0.0}, 'support': {'support': 783, 'agreement': 185, 'direct_attack': 150, 'undercutter_attack': 137, 'partial': 93}, 'micro_avg': {'precision': 0.11053412462908012, 'recall': 0.11053412462908012, 'f1': 0.11053412462908012, 'support': None}, 'macro_avg': {'precision': 0.04483891801534838, 'recall': 0.21018004866180048, 'f1': 0.07279366782430283, 'support': None}, 'weighted_avg': {'precision': 0.023922239737178705, 'recall': 0.11053412462908012, 'f1': 0.038733362104575904, 'support': None}}
Loss: tensor(0.7909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2847, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7831, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7972, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7680, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6978, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6806, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4978, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0785, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5972, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5852, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3817, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8783, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8890, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6514, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8977, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6424, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3652, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9720, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1863, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6511, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0801, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1955, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0783, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5516, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4921, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5601, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9382, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9955, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9862, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7703, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5843, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1826, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4714, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9921, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7814, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4797, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8761, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5904, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5654, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5794, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3713, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1775, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7971, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5641, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2837, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6793, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7719, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6635, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6956, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6654, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7584, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2774, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5913, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1682, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8730, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6915, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1652, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0740, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7460, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3871, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2983, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6740, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4656, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7705, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4689, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4718, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3668, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7997, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3957, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9975, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8765, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8769, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5730, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8773, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4971, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0993, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5601, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2683, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7998, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1409, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4942, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5550, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6962, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1580, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8412, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3730, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5598, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4913, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5935, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6998, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0783, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3553, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1915, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8567, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2542, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5794, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3928, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6492, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4935, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6754, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6601, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9683, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6586, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 2---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7020057306590258, 'agreement': 0.3764705882352941, 'direct_attack': 0.13855421686746988, 'undercutter_attack': 0.11307420494699646, 'partial': 0.16129032258064516}, 'recall': {'support': 0.6257982120051085, 'agreement': 0.34594594594594597, 'direct_attack': 0.15333333333333332, 'undercutter_attack': 0.23357664233576642, 'partial': 0.053763440860215055}, 'f1': {'support': 0.6617150573936529, 'agreement': 0.3605633802816901, 'direct_attack': 0.14556962025316456, 'undercutter_attack': 0.1523809523809524, 'partial': 0.08064516129032258}, 'support': {'support': 783, 'agreement': 185, 'direct_attack': 150, 'undercutter_attack': 137, 'partial': 93}, 'micro_avg': {'precision': 0.45548961424332346, 'recall': 0.45548961424332346, 'f1': 0.45548961424332346, 'support': None}, 'macro_avg': {'precision': 0.2982790126578863, 'recall': 0.2824835148960739, 'f1': 0.2801748343199565, 'support': None}, 'weighted_avg': {'precision': 0.4974716947606867, 'recall': 0.45548961424332346, 'f1': 0.4710969946628397, 'support': None}}
Loss: tensor(0.1602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5831, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6722, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2556, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0831, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5714, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2705, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0797, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2654, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8922, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6777, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5481, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9733, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1601, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8843, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1994, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1738, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9713, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5486, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8967, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0553, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5801, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4995, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0748, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1560, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1652, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4885, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9972, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2817, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3720, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1871, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2713, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4740, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8796, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0915, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6706, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9997, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1904, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0667, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3985, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2513, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3874, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0545, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1774, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1671, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0763, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3819, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1872, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3831, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8753, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5738, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9957, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6831, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1983, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6511, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4646, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0674, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1467, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1766, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0654, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0955, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8704, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8831, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4868, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2714, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9740, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1616, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0695, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2786, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5739, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1701, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0981, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0657, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3797, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6978, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8857, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0785, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8693, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1694, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8438, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9898, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1558, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0921, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5953, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1843, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7827, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2927, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5408, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0618, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9443, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7442, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8980, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8529, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0367, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1940, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1805, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3594, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4721, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1741, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3868, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0590, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6531, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0912, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3932, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1896, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2948, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1983, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2852, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1678, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2875, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1319, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3654, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5900, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4985, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8755, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6701, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4762, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2693, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6769, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 3---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7713178294573644, 'agreement': 0.10526315789473684, 'direct_attack': 0.37142857142857144, 'undercutter_attack': 0.1114519427402863, 'partial': 0.3448275862068966}, 'recall': {'support': 0.2538265306122449, 'agreement': 0.010869565217391304, 'direct_attack': 0.08666666666666667, 'undercutter_attack': 0.7956204379562044, 'partial': 0.21505376344086022}, 'f1': {'support': 0.38195777351247606, 'agreement': 0.01970443349753695, 'direct_attack': 0.14054054054054055, 'undercutter_attack': 0.1955156950672646, 'partial': 0.26490066225165565}, 'support': {'support': 784, 'agreement': 184, 'direct_attack': 150, 'undercutter_attack': 137, 'partial': 93}, 'micro_avg': {'precision': 0.25445103857566764, 'recall': 0.25445103857566764, 'f1': 0.25445103857566764, 'support': None}, 'macro_avg': {'precision': 0.3408578175455711, 'recall': 0.27240739277867354, 'f1': 0.20052382097389473, 'support': None}, 'weighted_avg': {'precision': 0.5394167409007059, 'recall': 0.25445103857566764, 'f1': 0.27862240585462045, 'support': None}}
Loss: tensor(0.2600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6891, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4779, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0665, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3502, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0781, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2844, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0809, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1925, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5636, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0662, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2978, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1669, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2306, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5650, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1332, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1506, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3551, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3569, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2864, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8585, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3974, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9878, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0701, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5445, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2403, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6987, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0955, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5962, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5607, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1820, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0885, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6970, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1625, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1806, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2724, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4798, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1880, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2373, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0720, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3768, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3494, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0481, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1802, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7837, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0697, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0608, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0736, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7956, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0797, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7000, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3588, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2634, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3903, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6414, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1898, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2978, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6923, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3711, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5765, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1880, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0522, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1728, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0455, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6483, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8971, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4776, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1479, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0498, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0427, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0752, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2374, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1694, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2816, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7524, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0654, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1825, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7525, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1813, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4856, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6484, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0983, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4811, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1941, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4926, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3940, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2758, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5611, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2997, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8851, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1937, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0279, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8889, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0774, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0694, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1917, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3272, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0670, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4769, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2989, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9601, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1912, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4619, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1576, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2735, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6743, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4934, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0782, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2792, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1774, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2920, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7978, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3991, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5707, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1628, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0673, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2865, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6423, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1885, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4986, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1954, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3962, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0806, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1698, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0829, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1796, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3651, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1643, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8555, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8873, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0996, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2680, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2882, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6759, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4686, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0828, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3485, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3526, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9815, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0971, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2887, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3774, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3482, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2905, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0843, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5459, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1562, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0931, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2854, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1898, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2983, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0376, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1884, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0547, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1846, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0769, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5417, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1388, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 4---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6998706338939198, 'agreement': 0.189873417721519, 'direct_attack': 0.25, 'undercutter_attack': 0.11290322580645161, 'partial': 0.2962962962962963}, 'recall': {'support': 0.6900510204081632, 'agreement': 0.08108108108108109, 'direct_attack': 0.013422818791946308, 'undercutter_attack': 0.35766423357664234, 'partial': 0.17204301075268819}, 'f1': {'support': 0.6949261400128453, 'agreement': 0.11363636363636365, 'direct_attack': 0.025477707006369428, 'undercutter_attack': 0.17162872154115585, 'partial': 0.21768707482993196}, 'support': {'support': 784, 'agreement': 185, 'direct_attack': 149, 'undercutter_attack': 137, 'partial': 93}, 'micro_avg': {'precision': 0.4621661721068249, 'recall': 0.4621661721068249, 'f1': 0.4621661721068249, 'support': None}, 'macro_avg': {'precision': 0.30978871474363734, 'recall': 0.26285243292210425, 'f1': 0.24467120140533324, 'support': None}, 'weighted_avg': {'precision': 0.49265464150026234, 'recall': 0.4621661721068249, 'f1': 0.45504379243106, 'support': None}}
Loss: tensor(0.7691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0463, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0294, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0468, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0943, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6315, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0441, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2505, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7796, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1565, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0472, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4747, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0324, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5631, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0617, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0900, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0713, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0976, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5999, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2956, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0899, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8602, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1998, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0746, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1579, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1849, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0496, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4363, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0610, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0893, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0311, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0444, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1647, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5837, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1731, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0940, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3977, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0869, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0520, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0635, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1813, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0606, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1384, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2956, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2534, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2796, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3898, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1343, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0756, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8640, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9870, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3474, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5945, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0546, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1705, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2660, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2866, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4990, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0537, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0541, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2971, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0972, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3422, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3908, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3958, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0411, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8573, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0764, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0639, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4612, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0320, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4723, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2914, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2791, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0589, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1638, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1712, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2900, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0845, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0799, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0532, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0642, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0912, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1946, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6883, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0557, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7902, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0623, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0900, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0694, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1655, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9803, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0340, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0710, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0807, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0293, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4738, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0715, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4426, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1683, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5933, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4649, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0982, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2271, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0688, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0671, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0844, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8599, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1630, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1470, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4487, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1834, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1842, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1432, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0664, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2821, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0359, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1410, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1963, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2823, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2988, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0276, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1229, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2507, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0330, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3543, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0366, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2964, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1530, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1601, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0575, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0389, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0192, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2940, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2275, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0488, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2841, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0203, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0892, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0690, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1685, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0833, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1609, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1944, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3328, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2778, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0538, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2800, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0843, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1789, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9836, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0322, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7808, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3581, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5952, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3480, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1652, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0544, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0648, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2326, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6992, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0956, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1927, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0209, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0515, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0497, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0621, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0858, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7449, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0773, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0433, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0512, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 5---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.7182044887780549, 'agreement': 0.24444444444444444, 'direct_attack': 0.21656050955414013, 'undercutter_attack': 0.16580310880829016, 'partial': 0.16037735849056603}, 'recall': {'support': 0.735632183908046, 'agreement': 0.11891891891891893, 'direct_attack': 0.22666666666666666, 'undercutter_attack': 0.23357664233576642, 'partial': 0.1827956989247312}, 'f1': {'support': 0.7268138801261829, 'agreement': 0.16, 'direct_attack': 0.2214983713355049, 'undercutter_attack': 0.19393939393939397, 'partial': 0.17085427135678388}, 'support': {'support': 783, 'agreement': 185, 'direct_attack': 150, 'undercutter_attack': 137, 'partial': 93}, 'micro_avg': {'precision': 0.505192878338279, 'recall': 0.505192878338279, 'f1': 0.505192878338279, 'support': None}, 'macro_avg': {'precision': 0.30107798201509917, 'recall': 0.29951802215082585, 'f1': 0.29462118335157317, 'support': None}, 'weighted_avg': {'precision': 0.5027377845808001, 'recall': 0.505192878338279, 'f1': 0.5002812819324962, 'support': None}}
Loss: tensor(0.0355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1790, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4493, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0559, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5661, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1402, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0960, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0289, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0257, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0737, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2145, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0242, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3645, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0334, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6521, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1368, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0910, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0595, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0454, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0393, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0705, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0375, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1511, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0381, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0500, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0592, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0386, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3900, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0966, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0519, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0918, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0458, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0178, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2586, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0400, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0453, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0339, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1475, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0729, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0405, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0709, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2564, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1198, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2419, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0478, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1822, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1796, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0662, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0835, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1604, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0274, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2396, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0578, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2671, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0416, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3503, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0261, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1517, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1548, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0691, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0473, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0490, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0196, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0222, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0349, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4895, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3287, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0425, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1767, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0399, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0795, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0901, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0431, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0772, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0401, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0508, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1395, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3298, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0354, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1898, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3771, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0267, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0879, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0246, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1853, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6951, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0413, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0364, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0804, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3377, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0979, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0561, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0233, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1725, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0295, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1969, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0850, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0653, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0291, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0380, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1392, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0307, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0536, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3890, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0415, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1708, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0461, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1187, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8213, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0292, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0810, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0344, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6329, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0232, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9489, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9843, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0552, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0788, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0684, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0342, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0374, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4770, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0593, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8959, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0692, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0572, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1658, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1888, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2624, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1826, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0909, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0671, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1940, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0288, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1734, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0158, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7894, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0341, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3699, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0397, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0191, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0321, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 6---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6826029216467463, 'agreement': 0.2631578947368421, 'direct_attack': 0.2047244094488189, 'undercutter_attack': 0.11261261261261261, 'partial': 0.26595744680851063}, 'recall': {'support': 0.6564495530012772, 'agreement': 0.21621621621621623, 'direct_attack': 0.17333333333333334, 'undercutter_attack': 0.18248175182481752, 'partial': 0.26881720430107525}, 'f1': {'support': 0.6692708333333333, 'agreement': 0.23738872403560832, 'direct_attack': 0.1877256317689531, 'undercutter_attack': 0.13927576601671307, 'partial': 0.267379679144385}, 'support': {'support': 783, 'agreement': 185, 'direct_attack': 150, 'undercutter_attack': 137, 'partial': 93}, 'micro_avg': {'precision': 0.46735905044510384, 'recall': 0.46735905044510384, 'f1': 0.46735905044510384, 'support': None}, 'macro_avg': {'precision': 0.3058110570507061, 'recall': 0.2994596117353439, 'f1': 0.30020812685979853, 'support': None}, 'weighted_avg': {'precision': 0.4851876335861724, 'recall': 0.46735905044510384, 'f1': 0.4748233763476617, 'support': None}}
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0200, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0924, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0886, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0296, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0345, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1420, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0256, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0540, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0596, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0832, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0371, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0855, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2369, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0614, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0818, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0687, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1240, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1388, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0165, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0539, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0167, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0549, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0968, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1357, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0830, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7620, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5672, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0181, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0144, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0352, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0249, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0378, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0582, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0280, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0147, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0235, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0462, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1282, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0346, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2962, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0675, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0277, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0327, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2877, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0266, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0347, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0571, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0533, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0787, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4801, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0501, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0355, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0208, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0911, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0469, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0629, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0603, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0217, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2535, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1456, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0605, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0146, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0477, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0205, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0243, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0659, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0262, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1566, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.4210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0385, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0251, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8681, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1812, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0331, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0570, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1434, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3871, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0254, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0627, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0197, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0270, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0260, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0716, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0215, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0365, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4495, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0237, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0236, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0435, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0194, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0193, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0466, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0518, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0447, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2720, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0568, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0136, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0360, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0226, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0180, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2666, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3644, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0309, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0247, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0106, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0255, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0362, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0211, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0304, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0265, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0316, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0839, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0317, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0421, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0227, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0591, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1262e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0299, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0314, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7145e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0135, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0457, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0228, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0290, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1303, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0150, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0301, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0523, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0285, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0745, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1554, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5439, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0210, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0125, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0450, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3212, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1305, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0984, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0221, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0100, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0351, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3760, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0446, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0437, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0086, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0224, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0310, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1587, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0404, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0407, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5583, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0471, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0890, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0663, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7245, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5898, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0387, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0510, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5643e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0361, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.4726, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 7---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6805411030176899, 'agreement': 0.41509433962264153, 'direct_attack': 0.22972972972972974, 'undercutter_attack': 0.12601626016260162, 'partial': 0.2857142857142857}, 'recall': {'support': 0.8341836734693877, 'agreement': 0.11891891891891893, 'direct_attack': 0.11333333333333333, 'undercutter_attack': 0.22794117647058823, 'partial': 0.043010752688172046}, 'f1': {'support': 0.749570200573066, 'agreement': 0.18487394957983194, 'direct_attack': 0.1517857142857143, 'undercutter_attack': 0.16230366492146595, 'partial': 0.07476635514018691}, 'support': {'support': 784, 'agreement': 185, 'direct_attack': 150, 'undercutter_attack': 136, 'partial': 93}, 'micro_avg': {'precision': 0.5400593471810089, 'recall': 0.5400593471810089, 'f1': 0.5400593471810089, 'support': None}, 'macro_avg': {'precision': 0.34741914364938975, 'recall': 0.26747757097608005, 'f1': 0.264659976900053, 'support': None}, 'weighted_avg': {'precision': 0.5107609621728928, 'recall': 0.5400593471810089, 'f1': 0.4997471398529426, 'support': None}}
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0391, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0162, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2859, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8679, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0358, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0166, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0286, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0269, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0096, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0465, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0268, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0163, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0297, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0139, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0398, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0861, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0350, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0218, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0128, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5428, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0615, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0133, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1614e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0241, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0126, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0333, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1881, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0448, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0406, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0259, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0138, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7792e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0244, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1700, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0318, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5347e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0353, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0248, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0370, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0258, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0337, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4068e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0177, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0323, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0207, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0142, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0717, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0252, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0348, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0278, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0206, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0120, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1509, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0149, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0140, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0220, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0185, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0159, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0116, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0075, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0777, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7730e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0091, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0174, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2325, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0124, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0440, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0175, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0749, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0131, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3736e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0216, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0263, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0155, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0189, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0372, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0394, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3443e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0110, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0264, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0172, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0112, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7045e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0143, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5683e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1973, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0156, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0300, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0253, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0231, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0527, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7388e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 8---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6936416184971098, 'agreement': 0.28313253012048195, 'direct_attack': 0.2459016393442623, 'undercutter_attack': 0.14193548387096774, 'partial': 0.15}, 'recall': {'support': 0.7662835249042146, 'agreement': 0.25405405405405407, 'direct_attack': 0.2, 'undercutter_attack': 0.16058394160583941, 'partial': 0.06451612903225806}, 'f1': {'support': 0.7281553398058254, 'agreement': 0.2678062678062678, 'direct_attack': 0.22058823529411764, 'undercutter_attack': 0.1506849315068493, 'partial': 0.09022556390977443}, 'support': {'support': 783, 'agreement': 185, 'direct_attack': 150, 'undercutter_attack': 137, 'partial': 93}, 'micro_avg': {'precision': 0.5229970326409495, 'recall': 0.5229970326409495, 'f1': 0.5229970326409495, 'support': None}, 'macro_avg': {'precision': 0.30292225436656434, 'recall': 0.2890875299192732, 'f1': 0.29149206766456687, 'support': None}, 'weighted_avg': {'precision': 0.49390305085125236, 'recall': 0.5229970326409495, 'f1': 0.5057958746040696, 'support': None}}
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0113, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0504, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8959e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0092, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0312, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0988e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0067, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0818e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7246e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5430e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6066e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3574, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2888e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9598e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3319e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6476e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0109, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9497e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0169, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9798e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0179, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0104, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2262e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6659e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1701, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9495e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8839e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6894e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9627e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2050e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0182, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1021e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0115, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0714, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0122, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5600, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2308, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6971e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0424e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8868e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0119, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9064e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0105, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0394e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0281, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4841e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2826e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0093, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6459e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7983e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7287e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0080, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0083, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 9---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6927437641723356, 'agreement': 0.38961038961038963, 'direct_attack': 0.24503311258278146, 'undercutter_attack': 0.11702127659574468, 'partial': 0.18}, 'recall': {'support': 0.7803320561941252, 'agreement': 0.16216216216216217, 'direct_attack': 0.24666666666666667, 'undercutter_attack': 0.16058394160583941, 'partial': 0.0967741935483871}, 'f1': {'support': 0.733933933933934, 'agreement': 0.22900763358778625, 'direct_attack': 0.24584717607973425, 'undercutter_attack': 0.13538461538461538, 'partial': 0.1258741258741259}, 'support': {'support': 783, 'agreement': 185, 'direct_attack': 150, 'undercutter_attack': 137, 'partial': 93}, 'micro_avg': {'precision': 0.5259643916913946, 'recall': 0.5259643916913946, 'f1': 0.5259643916913946, 'support': None}, 'macro_avg': {'precision': 0.32488170859225024, 'recall': 0.2893038040354361, 'f1': 0.29400949697203915, 'support': None}, 'weighted_avg': {'precision': 0.5074355869479934, 'recall': 0.5259643916913946, 'f1': 0.5075428374702944, 'support': None}}
Loss: tensor(6.8758e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0405e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9657e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0336, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0727e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0838, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0052e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7597, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0085, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0222e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9063e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0079, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6067e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8124e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0068, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0829e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0173e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6317e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6652e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0061, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8486e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0087, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9355e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0494e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4750e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0102, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0073, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9588e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3461e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8338, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0057, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0624e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7760e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3097e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5590e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0064, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9274e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2571e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9437e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0060, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6325e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5913e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0078, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0076, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0133e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2625e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4470e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2359e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1251e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2353e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2915e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6812e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0058, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4187e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4018e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1181e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0050, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 10---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.691358024691358, 'agreement': 0.3486238532110092, 'direct_attack': 0.248, 'undercutter_attack': 0.11173184357541899, 'partial': 0.1590909090909091}, 'recall': {'support': 0.7857142857142857, 'agreement': 0.20652173913043478, 'direct_attack': 0.20666666666666667, 'undercutter_attack': 0.145985401459854, 'partial': 0.07526881720430108}, 'f1': {'support': 0.7355223880597015, 'agreement': 0.25938566552901027, 'direct_attack': 0.22545454545454544, 'undercutter_attack': 0.12658227848101264, 'partial': 0.1021897810218978}, 'support': {'support': 784, 'agreement': 184, 'direct_attack': 150, 'undercutter_attack': 137, 'partial': 93}, 'micro_avg': {'precision': 0.5281899109792285, 'recall': 0.5281899109792285, 'f1': 0.5281899109792285, 'support': None}, 'macro_avg': {'precision': 0.31176092611373907, 'recall': 0.28403138203510847, 'f1': 0.28982693170923357, 'support': None}, 'weighted_avg': {'precision': 0.49960993877161525, 'recall': 0.5281899109792285, 'f1': 0.5081899987398077, 'support': None}}
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0939, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5339e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2979e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4076e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6812e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.2071, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8041e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5489e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5438e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5771e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0222e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0637, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2432e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8214e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3461e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0048, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4098e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9739e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8665e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4743e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1625e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0052, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0442e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9970e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5501e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0072, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9536e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2108e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5511e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6788e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5922e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4530e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0987e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8852e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2813e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3571e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6701e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5822e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1614e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0062, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9707e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4299e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1616e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8489e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5577e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4290e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3037e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6500e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2492e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6115e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0412e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3591e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3207e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2246e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6104e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9758e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9586e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2978e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0036, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0989e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1978e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1351e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3078e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7094e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4339e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3388e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3669e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2310e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0084, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2595e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8513e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6793e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0345e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4371e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 11---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.687842278203724, 'agreement': 0.37755102040816324, 'direct_attack': 0.27586206896551724, 'undercutter_attack': 0.10674157303370786, 'partial': 0.13953488372093023}, 'recall': {'support': 0.8010204081632653, 'agreement': 0.2, 'direct_attack': 0.21333333333333335, 'undercutter_attack': 0.1386861313868613, 'partial': 0.06521739130434782}, 'f1': {'support': 0.7401296405421333, 'agreement': 0.2614840989399293, 'direct_attack': 0.2406015037593985, 'undercutter_attack': 0.12063492063492064, 'partial': 0.08888888888888889}, 'support': {'support': 784, 'agreement': 185, 'direct_attack': 150, 'undercutter_attack': 137, 'partial': 92}, 'micro_avg': {'precision': 0.5356083086053413, 'recall': 0.5356083086053413, 'f1': 0.5356083086053413, 'support': None}, 'macro_avg': {'precision': 0.3175063648664085, 'recall': 0.28365145283756155, 'f1': 0.2903478105530541, 'support': None}, 'weighted_avg': {'precision': 0.502934273026707, 'recall': 0.5356083086053413, 'f1': 0.5114474658439103, 'support': None}}
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2108e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2010e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7850e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0054, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0887e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5026e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2625e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0181e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6872e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7952e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8859e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3744e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7881e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3069e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2068e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6742e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6699e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9929e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1623e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2736e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7840e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0049, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3190e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4843e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4914e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5219e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3188e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1159e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0524e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8547e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5096e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4602e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5447e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8117, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3088e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.1065, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0053, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9809e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3431e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3793e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6407e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8495e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2169e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5448e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0827e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5883e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8707e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4531e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6430e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6608e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4472e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2311e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7822e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8102e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5985e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8546e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9355e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0200e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2997e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7246e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8020e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5326e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1222e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8516e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5135e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7489e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0131e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9271e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7558e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6206e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4199e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6043e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8150e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9233e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9809e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2928e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9243e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8021e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2695e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8689e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5923e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2149e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8395e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6295e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2967e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6971e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3905e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0512e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1825e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2229e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6022e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3963e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5760e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8750e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3410e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1774e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2371e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1444e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8356e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1019e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2066, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7638e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0824, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7306e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8518e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4823e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6931e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.1499, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2794e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3866e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2655e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 12---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.693621867881549, 'agreement': 0.34782608695652173, 'direct_attack': 0.2631578947368421, 'undercutter_attack': 0.11413043478260869, 'partial': 0.16666666666666666}, 'recall': {'support': 0.7767857142857143, 'agreement': 0.17391304347826086, 'direct_attack': 0.26666666666666666, 'undercutter_attack': 0.15328467153284672, 'partial': 0.07526881720430108}, 'f1': {'support': 0.7328519855595669, 'agreement': 0.23188405797101447, 'direct_attack': 0.26490066225165565, 'undercutter_attack': 0.13084112149532712, 'partial': 0.1037037037037037}, 'support': {'support': 784, 'agreement': 184, 'direct_attack': 150, 'undercutter_attack': 137, 'partial': 93}, 'micro_avg': {'precision': 0.5259643916913946, 'recall': 0.5259643916913946, 'f1': 0.5259643916913946, 'support': None}, 'macro_avg': {'precision': 0.3170805902048376, 'recall': 0.2891837826335579, 'f1': 0.29283630619625356, 'support': None}, 'weighted_avg': {'precision': 0.5032708443582182, 'recall': 0.5259643916913946, 'f1': 0.5078096444899256, 'support': None}}
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4228e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9758e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8374e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6237e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5014e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7306e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0070e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0485e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8926, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2221e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4690e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8334e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9846e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4387e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5698e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8181e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0212e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9546e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6546e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3512e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2089e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0049e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4759e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0351e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8405e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8275e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0051, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7145e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0044, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1541e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8173e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3780, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1030e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1847e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4521e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9010e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9513e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0047, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7913e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2138e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7800e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7377e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6146e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1535e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9881e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0491, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3381e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2945e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9971e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7190e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9092e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7558e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0037, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6368e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9907e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0756e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0554e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6327e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1160e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4530e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4409e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6608e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2816e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3076e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1414e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0059, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9345e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7219, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7175e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1938e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0384e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0524e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3297e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9233e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0055, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2300e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4629e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2655e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0694e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3745e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0745e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0633, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7184e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6115e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4148e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2695e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3108e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6561e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2259e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7345e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9758e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8810e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7671e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6881e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1502e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6872e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4459e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0957e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6157e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8658e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3191e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6843e-05, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 13---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6943820224719102, 'agreement': 0.33043478260869563, 'direct_attack': 0.25806451612903225, 'undercutter_attack': 0.11560693641618497, 'partial': 0.15217391304347827}, 'recall': {'support': 0.789272030651341, 'agreement': 0.20540540540540542, 'direct_attack': 0.21333333333333335, 'undercutter_attack': 0.145985401459854, 'partial': 0.07526881720430108}, 'f1': {'support': 0.7387925881649732, 'agreement': 0.25333333333333335, 'direct_attack': 0.23357664233576642, 'undercutter_attack': 0.12903225806451613, 'partial': 0.10071942446043167}, 'support': {'support': 783, 'agreement': 185, 'direct_attack': 150, 'undercutter_attack': 137, 'partial': 93}, 'micro_avg': {'precision': 0.5304154302670623, 'recall': 0.5304154302670623, 'f1': 0.5304154302670623, 'support': None}, 'macro_avg': {'precision': 0.3101324341338602, 'recall': 0.2858529976108469, 'f1': 0.2910908492718041, 'support': None}, 'weighted_avg': {'precision': 0.4996524925812538, 'recall': 0.5304154302670623, 'f1': 0.5099570366319469, 'support': None}}
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9739e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1018e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8808e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6251e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5168e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5186e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7856e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4430e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6464, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6558e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3844e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6952e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7475e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0039, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5441e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4569e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9376e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7173, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1916e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0557e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3715e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6843e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5851e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8004e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0565e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0778e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5017e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7333e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3906e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6993e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2231e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2834e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9798e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9322e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4500e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9818e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8880e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4047e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9928e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6930e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1947e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4865e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7739e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1550e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9770e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0391e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2159e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7005e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9243e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9162e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4765e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8928e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9961, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1462e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7293e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1040e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8324e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9222e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2207e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7620e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3554e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2773e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4743e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7588e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6467e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9755e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1078e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7318e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4784e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0515e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2533e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9634e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5940e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7133e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6840e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2218e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3290e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6091e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1633e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2149e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6579e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2089e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4368e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0581e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5296e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7397e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6036e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2543e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0603e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9446e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3521e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5650e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9445e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7415e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8586e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8889e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2510e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1654e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0505e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3815e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1899e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5620e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2584e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9840e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1281e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2403e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5864e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5005e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1462e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9910e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0696, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7938e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6609e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2159e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2955e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0342e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5827e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7415e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5538e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9707e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7294e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2298e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9504e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5662e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8275e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6606e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0041, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8578e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 14---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6928251121076233, 'agreement': 0.36082474226804123, 'direct_attack': 0.2777777777777778, 'undercutter_attack': 0.11627906976744186, 'partial': 0.16279069767441862}, 'recall': {'support': 0.789272030651341, 'agreement': 0.1891891891891892, 'direct_attack': 0.26666666666666666, 'undercutter_attack': 0.145985401459854, 'partial': 0.07526881720430108}, 'f1': {'support': 0.7379104477611941, 'agreement': 0.24822695035460995, 'direct_attack': 0.27210884353741494, 'undercutter_attack': 0.12944983818770225, 'partial': 0.10294117647058824}, 'support': {'support': 783, 'agreement': 185, 'direct_attack': 150, 'undercutter_attack': 137, 'partial': 93}, 'micro_avg': {'precision': 0.5341246290801187, 'recall': 0.5341246290801187, 'f1': 0.5341246290801187, 'support': None}, 'macro_avg': {'precision': 0.3220994799190605, 'recall': 0.2932764210342704, 'f1': 0.2981274512623019, 'support': None}, 'weighted_avg': {'precision': 0.5059132597985043, 'recall': 0.5341246290801187, 'f1': 0.5132272627497849, 'support': None}}
Loss: tensor(9.2736e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1532e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1117e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8659e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6490e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6591e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3926e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1916e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4751e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7004e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9452e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8191e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8999e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6076e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3674e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9755e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5883e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0727e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3321e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2462e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5297e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1352e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8496e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9119e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8648e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3573e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8556e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3397e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9285e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7708e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2752e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2089e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4612e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8458e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5538e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7457e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8111e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8093e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9928e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3682e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1400e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5498e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3240e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0111e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8788e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4198e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7217e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0624e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6388e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2250e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1943e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0379, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6105e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2525e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8959e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1826e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1514e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3872e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7596e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0133e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8425e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1595e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0611e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6627e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8850e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8083e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1393e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9815e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7506e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9434e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0928e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0182e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2251e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4199e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2207e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3258e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8807e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8183, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8458e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0058e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5480e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2411e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2867e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9434e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5741e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9113e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2986e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4045e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9567e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2865e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4621e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1462e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5607e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3107e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4275e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7155e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0897, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3157e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3391e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9706e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2099e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8525e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7195e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8939e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9897e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1020e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0685e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5758e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4835e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4460e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3894e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9072e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1423e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6537e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3342e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6883e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4923e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9213e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7983e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8072e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7539e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7432e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9988e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0032, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1005e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0373e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5508e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9859e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2555e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8980e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5096e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3025e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6560e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5213e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5328e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1965e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8375e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5499e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4905e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7306e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6739e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3056, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1574e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7293e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6436, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9997e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5386e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6822e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7931e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3270e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6258e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5135e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9758e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 15---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6903440621531631, 'agreement': 0.336283185840708, 'direct_attack': 0.2689075630252101, 'undercutter_attack': 0.11627906976744186, 'partial': 0.13953488372093023}, 'recall': {'support': 0.7943805874840357, 'agreement': 0.20540540540540542, 'direct_attack': 0.21333333333333335, 'undercutter_attack': 0.145985401459854, 'partial': 0.06451612903225806}, 'f1': {'support': 0.7387173396674583, 'agreement': 0.2550335570469799, 'direct_attack': 0.23791821561338292, 'undercutter_attack': 0.12944983818770225, 'partial': 0.08823529411764705}, 'support': {'support': 783, 'agreement': 185, 'direct_attack': 150, 'undercutter_attack': 137, 'partial': 93}, 'micro_avg': {'precision': 0.5326409495548962, 'recall': 0.5326409495548962, 'f1': 0.5326409495548962, 'support': None}, 'macro_avg': {'precision': 0.31026975290149067, 'recall': 0.2847241713429773, 'f1': 0.28987084892663406, 'support': None}, 'weighted_avg': {'precision': 0.4985125380151523, 'recall': 0.5326409495548962, 'f1': 0.5098109254747589, 'support': None}}
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7415e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1967e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1021e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2925e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8483e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9397e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1762e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2674e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1411e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8547e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1687e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3966e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6247e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8729e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2059e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0732, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3036e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0473e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2341e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8702, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5155e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9392e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0611e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2825e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4520e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6294e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3744e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4335e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3844e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7496e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2995e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8576e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2653e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0763e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2177e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1251e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5316e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8416e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4128e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8184e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9200e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9716e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9828e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8919e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0922e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5105e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7093e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4522e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2752e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0896e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7839e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0745e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9766e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9252e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4450e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8253e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1501e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1784e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7648e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9240e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7000e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3351e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3821e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0490e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2337e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4828e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2927e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9727e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6143e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3349e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5174e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0859e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.6383, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0936e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6264e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5731e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3215e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0040, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1687e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0218e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5671e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0282e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9755e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0043, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5824e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7778e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6342e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2835e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0035, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4365e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9697e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7105e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3258e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9141, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4759e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0058e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0061e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0038, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7800e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3366e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6166e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6251e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2246e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9676e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4275e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0243e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5580e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6468e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8354e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2752e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6146e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2796e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1722e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9392e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0663e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6985e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4209e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2047e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5165e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5630e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9997e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2319e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3250e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7324e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2946e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0026, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2561e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4045e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0330e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7275e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1069e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8081e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6901e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1541e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9128e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3469e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5317e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9937e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4984e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4941e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9303e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5561e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7042e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1916e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4704e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2954e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6257e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7114e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0066e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5326e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4520e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6397e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4054e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9052e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7091e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9019e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0455e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2302, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4145e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5486e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4508e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9612e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9283e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5680e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5858e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7811e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8689e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7983e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3331e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8132e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0375e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7094e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7445e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2825e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0805e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6364e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5792e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3751e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9885e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1662e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0727e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7921e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8647e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8747e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1381e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7648e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3893e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 16---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6914285714285714, 'agreement': 0.42105263157894735, 'direct_attack': 0.25, 'undercutter_attack': 0.11299435028248588, 'partial': 0.16666666666666666}, 'recall': {'support': 0.7726692209450831, 'agreement': 0.17297297297297298, 'direct_attack': 0.2866666666666667, 'undercutter_attack': 0.145985401459854, 'partial': 0.08602150537634409}, 'f1': {'support': 0.729794933655006, 'agreement': 0.24521072796934867, 'direct_attack': 0.26708074534161497, 'undercutter_attack': 0.1273885350318471, 'partial': 0.11347517730496454}, 'support': {'support': 783, 'agreement': 185, 'direct_attack': 150, 'undercutter_attack': 137, 'partial': 93}, 'micro_avg': {'precision': 0.5252225519287834, 'recall': 0.5252225519287834, 'f1': 0.5252225519287834, 'support': None}, 'macro_avg': {'precision': 0.32842844399133425, 'recall': 0.2928631534841842, 'f1': 0.2965900238605563, 'support': None}, 'weighted_avg': {'precision': 0.5102103369876685, 'recall': 0.5252225519287834, 'f1': 0.5080570848042776, 'support': None}}
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4863e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0200e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8454e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4570e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8210e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4199e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5737e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3957e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4932e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1593e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0563, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6508e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4850e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3751e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8841e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6204e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5922e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8961e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1822e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5317e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8262e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4008e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5153e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8789e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5083e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8847e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7242e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0251e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0799e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2736e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4387e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8749e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5449e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1968e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6842e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1645e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0897e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3042e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2754e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8323e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8725e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7566e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9422e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9452e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9949, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9879e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3237e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1260e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9647e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6409e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4723e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4790e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4214e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8486e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1671e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5788e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3401e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9403e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7849e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9808e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3379e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4863e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3976e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1807e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3016e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9383e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7947e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1701e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5758e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4093e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2865e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4420e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5658e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1624e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2398e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2513e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2119e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9979e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6809e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9028e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2891e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3609e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7164e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1986e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3375e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5438e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.7452, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8197e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0079e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4356e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7124e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9789e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9000e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4855e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4904e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8816e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5065e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0767e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4729e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9227e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2674e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9262e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3730e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0888e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6697e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7499e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6962e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7033e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5166e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3694e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6739e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0239e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1956e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3321e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3094e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5053e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3336e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7226e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4318e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2676e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5167e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4569e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1696e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4147e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1247e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3773e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9292e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2613e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0218e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7035e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7781e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1351e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7778e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8859e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0139e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3678e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4952e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7201, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6285e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2604e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4300e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4872e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1420e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2238e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7696e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1269e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6942e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0615e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0468e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3570e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9424e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2964e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8332e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3612e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6627e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3833e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3730e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9552e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3390, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9666e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4248e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6736e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1965e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4396e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4611e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5225e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0542e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3669e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3570e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7234e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9565e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7497e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4863e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3885e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5849e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0445e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1238e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6848e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7487e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7363e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6766e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4002e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9849e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9400e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6697e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 17---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6923963133640553, 'agreement': 0.3333333333333333, 'direct_attack': 0.26277372262773724, 'undercutter_attack': 0.11538461538461539, 'partial': 0.14893617021276595}, 'recall': {'support': 0.7675606641123882, 'agreement': 0.20540540540540542, 'direct_attack': 0.24, 'undercutter_attack': 0.15328467153284672, 'partial': 0.07526881720430108}, 'f1': {'support': 0.7280436099333737, 'agreement': 0.2541806020066889, 'direct_attack': 0.2508710801393728, 'undercutter_attack': 0.13166144200626959, 'partial': 0.1}, 'support': {'support': 783, 'agreement': 185, 'direct_attack': 150, 'undercutter_attack': 137, 'partial': 93}, 'micro_avg': {'precision': 0.521513353115727, 'recall': 0.521513353115727, 'f1': 0.521513353115727, 'support': None}, 'macro_avg': {'precision': 0.3105648309845015, 'recall': 0.28830391165098823, 'f1': 0.292951346817141, 'support': None}, 'weighted_avg': {'precision': 0.4991749217821676, 'recall': 0.521513353115727, 'f1': 0.505971689558482, 'support': None}}
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4671e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1393e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5923e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4278e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5386e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0343e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4499e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8545e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1747e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0979e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9194e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6327e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9898e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5598e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8293e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3249e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6235e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1017e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6307e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7707e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5922e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6779e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1511e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8665e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0025, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5931e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7869e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1770e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2648e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4400e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8779e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8385e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9128e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8476, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0119e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6697e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9061e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9062e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6273e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0624e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0672e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8241e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9214e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6567e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4408e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5962e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2277e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9808e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1979e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1484e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7627e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4704e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2464e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5579e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0033, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9806e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2816e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0624e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5486e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1831e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2725e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.3528, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5131e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7801e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8689e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2419e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5065e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1282e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3578e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0223e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1148e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9655e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1523e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2654e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6597e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5568e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5416e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7584e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2592e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2734e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6035e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2389e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3894e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1653e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6839e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8777e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5101e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0049e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9514e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3633e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7445e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0157e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9262e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5689e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7748e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8750e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0088e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1883e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0434e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1238e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0848, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2271e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4426e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5040e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6519e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2976e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8283, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0152e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3582e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0930, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2648e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8213e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9694e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7880e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2037e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2713e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2561e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8859e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9413e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9037e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3306e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3630e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0261e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5274e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0978e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5425e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1943e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8665e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1238e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4681e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1463e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1188e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0187e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5131e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3410e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9119e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1008e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9906e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3215e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2813e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4985e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8150e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5849e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0918e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6243e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1756e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9776e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9564e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3643e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6013e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7032e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9161e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1451e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3330e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4266e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7354e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6075e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2579e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8734e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3058e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4015e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9524e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1564e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9838e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7826e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2077e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5638e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3185e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5304e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7751e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5319e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0200e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4396e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2926e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7929e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6064e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3148e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 18---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6906077348066298, 'agreement': 0.37894736842105264, 'direct_attack': 0.271523178807947, 'undercutter_attack': 0.12179487179487179, 'partial': 0.14634146341463414}, 'recall': {'support': 0.7971938775510204, 'agreement': 0.1945945945945946, 'direct_attack': 0.2733333333333333, 'undercutter_attack': 0.1386861313868613, 'partial': 0.06521739130434782}, 'f1': {'support': 0.7400828892835998, 'agreement': 0.2571428571428571, 'direct_attack': 0.2724252491694353, 'undercutter_attack': 0.1296928327645051, 'partial': 0.09022556390977443}, 'support': {'support': 784, 'agreement': 185, 'direct_attack': 150, 'undercutter_attack': 137, 'partial': 92}, 'micro_avg': {'precision': 0.5393175074183977, 'recall': 0.5393175074183977, 'f1': 0.5393175074183977, 'support': None}, 'macro_avg': {'precision': 0.3218429234490271, 'recall': 0.2938050656340315, 'f1': 0.29791387845403433, 'support': None}, 'weighted_avg': {'precision': 0.5062459318527659, 'recall': 0.5393175074183977, 'f1': 0.5153775008261294, 'support': None}}
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7929e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7778e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9340e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3915e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5516e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5750e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8232e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2481e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3774e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0635e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1026e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1602e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4720e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1695e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6843e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7808e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9923e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0291e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2056e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0678e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4802e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8522e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0576e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3327e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7636e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4914e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1635e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0394e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2700e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5222e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0685e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1310e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4802e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9819e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0866e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0564e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4205e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2246e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8537e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0502e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9876e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8063e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4830e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9323e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1798e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5237e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3874e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8012e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6295e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5659e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1744e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8889e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1593e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7486e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9655e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8946e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6791e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1108e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2250e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.3140e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4329e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6770e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1454e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8943e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5347e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9560e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9898e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7920e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7627e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3500e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2220e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8317e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0674e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0512e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4036e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6355e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1117e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5701e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6894e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8223e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9101e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0148e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7475e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1679e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4623e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8855e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1877e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4547e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3612e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2670e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2068e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.4709e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2389e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2572e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4084e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0430, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3518e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4692e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8847e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5156e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5153e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1126e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2016e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3418e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.8418, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7302e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5813e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7959e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4841e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1338e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4673e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3405e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8747e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1281e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8371e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2786e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6648e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0089, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1247e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2761e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1377e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4116e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8759e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0369e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3208e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9776e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4054e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2250e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8764e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9370e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3511e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6125e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3812e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1441e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6675e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7129e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4820e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3457e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2026e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2010e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0836e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7787e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9383e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8056e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0857e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5153e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0624e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5731e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6748e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8129e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7415e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9050e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6666e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6315e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4517e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9867e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6254e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5546e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7220e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6930e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6705e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5797e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0029, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7614e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0632e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8536e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3457e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9301e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5525e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5970e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9849e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1905e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5732e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3496e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3703e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9037e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9309e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0028, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9686e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6205e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1989e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6879e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6939e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1935e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4601e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0503e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6416e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4267e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0522e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1805e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6779e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6941e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5858e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3366e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3155e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9443e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0323e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9582e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6912e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6675e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9227e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8184, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4720e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8734e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2309e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4279e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7042e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2727, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0687e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1432e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9696e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3457e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7332e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9011e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1714e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7415e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2813e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0615e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1744e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4236e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4348e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6508e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3418e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8223e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2800e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0027, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1444e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1995e-05, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 19---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6883561643835616, 'agreement': 0.45454545454545453, 'direct_attack': 0.23404255319148937, 'undercutter_attack': 0.11428571428571428, 'partial': 0.16279069767441862}, 'recall': {'support': 0.7701149425287356, 'agreement': 0.16216216216216217, 'direct_attack': 0.29333333333333333, 'undercutter_attack': 0.145985401459854, 'partial': 0.07526881720430108}, 'f1': {'support': 0.7269439421338156, 'agreement': 0.23904382470119523, 'direct_attack': 0.2603550295857988, 'undercutter_attack': 0.1282051282051282, 'partial': 0.10294117647058824}, 'support': {'support': 783, 'agreement': 185, 'direct_attack': 150, 'undercutter_attack': 137, 'partial': 93}, 'micro_avg': {'precision': 0.5222551928783383, 'recall': 0.5222551928783383, 'f1': 0.5222551928783383, 'support': None}, 'macro_avg': {'precision': 0.3308041168161277, 'recall': 0.2893729313376773, 'f1': 0.2914978202193052, 'support': None}, 'weighted_avg': {'precision': 0.5111104202691581, 'recall': 0.5222551928783383, 'f1': 0.5041625375921631, 'support': None}}
Loss: tensor(7.3421e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8051e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5758e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0975e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9291e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5519e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.5876, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8171e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8924e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5924e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6978e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4478e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2406e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2581e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2661e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1217e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8362e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3209e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1846e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1533e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6494e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8453e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8344e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9594e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3863e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4508e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4063e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8310e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0212e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5810e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5480e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6206e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0520e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0022, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7060e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9058e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7493e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9192e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1381e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9325e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2915e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6576e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8704e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3145e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2592e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1925e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7505e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8535e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6485e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1301e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0784e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5728e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5404e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2633e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9403e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6546e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4798e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5598e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4245e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1188e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2917e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9577, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1308e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4759e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8494e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2943e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1148e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7932e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7950e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0196e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7102e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1037e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9564e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1583e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0898e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8335e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8574e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7657e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2912e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9746e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0482e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3824e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0006e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3107e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3669e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9525e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.6305e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6982e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1171e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1865e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6570e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6588e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2259e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2813e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6154e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6809e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5883e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9602e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8059e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7968e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2238e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5616e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3890e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3551e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1502e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8574e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6657e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8310e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3085e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0403e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0342e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.7438e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1770e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0641e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0853e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8924e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6870e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9301e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2471e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5819e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4556e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4590e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4275e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7462e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5416e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2825e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2519e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6961e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2823e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0622, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3185e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6861e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2103e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2973e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0745e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2822e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7363e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0423e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2513e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6251e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8747e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5879e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1553e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3025e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4971e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7847e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7830e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0686e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7856e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1935e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9361e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1653e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.8193e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3518e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4992e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0892e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0221e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4214e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7527e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3842e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7947e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4660e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0373e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4949e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8535e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0313, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3881e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7878e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8825e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2017e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1000e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7878e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2186e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7575e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5910e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7881e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.1020e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9854e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4076e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0806e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3851e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8141e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5313e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1118e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3127e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5610e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6570e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6273e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4396e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9868e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3400e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4184e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2108e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9673e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5304e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.8500e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9214e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0827e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0016, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3340e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9240e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6485e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9010e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2821e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4612e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6466e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9485e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8271e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8665e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9646e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1905e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9113e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1783e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6970e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7644e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9634e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.7531e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5200e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5070e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4832e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1452e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9473e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1065e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2791e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7584e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4962e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8059e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2561e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4115e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0672e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9162e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
			------------EPOCH 20---------------
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
Evaluating
				 {'precision': {'support': 0.6749482401656315, 'agreement': 0.4117647058823529, 'direct_attack': 0.2727272727272727, 'undercutter_attack': 0.10897435897435898, 'partial': 0.16666666666666666}, 'recall': {'support': 0.8316326530612245, 'agreement': 0.1891891891891892, 'direct_attack': 0.18, 'undercutter_attack': 0.125, 'partial': 0.07526881720430108}, 'f1': {'support': 0.7451428571428571, 'agreement': 0.2592592592592593, 'direct_attack': 0.21686746987951808, 'undercutter_attack': 0.11643835616438357, 'partial': 0.1037037037037037}, 'support': {'support': 784, 'agreement': 185, 'direct_attack': 150, 'undercutter_attack': 136, 'partial': 93}, 'micro_avg': {'precision': 0.5474777448071216, 'recall': 0.5474777448071216, 'f1': 0.5474777448071216, 'support': None}, 'macro_avg': {'precision': 0.32701624888325653, 'recall': 0.2802181318909429, 'f1': 0.28828232922994435, 'support': None}, 'weighted_avg': {'precision': 0.5019031859107522, 'recall': 0.5474777448071216, 'f1': 0.5119919468306314, 'support': None}}
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1463e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9937e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5174e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0135e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3268e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2155e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0654e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2510e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3284e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7190e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0070e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2200e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6848e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6778e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1165e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0784e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0321e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4599e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7605e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4862e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6039e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3950e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3994e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6093e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2276e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9543e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.6884e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8062e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3611e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4868e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7242e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8371e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2860e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7053e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1662e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9606e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0754e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6546e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1119e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0194e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9945e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8839e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9262e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6303e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9133e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3751e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2458e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6515e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7000e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5549e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0796e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8635e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5416e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8786e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1744e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2834e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.9549e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3551e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1794e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4253e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0702e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6980e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3560e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8144e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.0335, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4880e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.4227e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5853e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9904e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8293e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0363e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.0654e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7129e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2549e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8808e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6688e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7748e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1653e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5576e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9976e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8678e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8526e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0014, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5658e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0754e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5910e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.2631e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3822e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6908e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2224e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3449e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8816e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1099e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9400e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3400e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.1431e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6264e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8401e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8214e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8810e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3639e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0512e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2199e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6857e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0633e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7720e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9785e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.9997e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1634e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0918e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0118e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7154e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5962e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5577e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2519e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7293e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5307e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5468e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2648e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9646e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5529e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1459e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5153e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5356e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.9917e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3488e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5918e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2008e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2369e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3751e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3790e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6134e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8552e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2450e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5846e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.0142e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9425e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2331e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2935e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.0098e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7393e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2315e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6714e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.5286e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.3130e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9110e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.6869e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.3694e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.0105e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2474e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1472e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6939e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.5507e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3339e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5135e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6619e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1044e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1740e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7324e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3167e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6688e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4487e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.0270e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3621e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.6619e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.1558e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8223e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4084e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1411e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.3001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.8946e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.4599e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4677e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.1842e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8344e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.5797e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.8665e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0884e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9755e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2490e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2004e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0008e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2329e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8777e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.5445e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3911e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9642e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2428e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.8534e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2346e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3551e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2640e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.2211e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9681e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4328e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.6524e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.9585e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7428e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5001e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9612e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9573e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7415e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5698e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.2592e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7250e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5549e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9621e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1148e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4791e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9984e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.9106e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2750, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.5811e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.3277e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.9573e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.1057e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0012, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.9733e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.5225e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0371e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.8004e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.2795e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7021e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1229e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.7203e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6173e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7333e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3418e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.5244e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.1452e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7220e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.1429e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7072e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(8.2958e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2155e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.5399e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0010, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.3198e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.8426e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.4123e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.6557e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.2064e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.0735e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.7972e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7765e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.4853e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.6122e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.3072e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.8405e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.0394e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.9957e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.3245e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0015, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.6017e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.4572e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.6234e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.2073e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.9107, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.8808e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7749e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(4.3993e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(1.5927e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.7405e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.7182e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(9.4037e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.4253e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.7091e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0006, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(5.1260e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.2702e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(2.7341e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0002, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.2676, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(3.0944e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(7.7112e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0003, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0009, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(6.9363e-05, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss: tensor(0.0004, device='cuda:0', grad_fn=<DivBackward0>)
